In silico identification of cancer molecular signaling pathways and drug candidates

ABSTRACT

Disclosed is an in silico method to identify molecular signaling pathways that influence cancer development as well as therapeutic compounds with activity against them.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims benefit of U.S. Provisional Application No. 61/721,754, filed Nov. 2, 2012, which is hereby incorporated herein by reference in its entirety.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

This invention was made with Government Support under Grant No. CA76292 awarded by the National Institutes of Health. The Government has certain rights in the invention.

BACKGROUND

Ovarian cancer (OVCA) has the highest mortality of all gynecologic cancers (Siegel R, et al. CA Cancer J Clin. 2012 62(1):10-29). Although patients are initially sensitive to cytotoxic therapy (using platinum/taxane-based regimens), resistance to existing therapies develops in the majority of patients with OVCA (Baker V V. Hematol Oncol Clin North Am. 2003 17(4):977-88; Gadducci A, et al. Gynecol Oncol. 1998 68(2):150-5; Hansen H H, et al. Ann Oncol. 1993 4 Suppl 4:63-70; McGuire W P, et al. N Engl J Med. 1996 334(1):1-6). Once chemoresistance has developed, for most patients, overall survival is extremely short (Herrin V E, et al. Semin Surg Oncol. 1999 17(3):181-8). The lack of progress in improvement in cure rates for this disease is somewhat reflective of an incomplete understanding of the molecular basis to disease development. Improvements in understanding the molecular basis to ovarian carcinogenesis will hopefully lead to the identification of more active therapies.

SUMMARY

Disclosed is an in silico strategy that identifies 1) new cancer therapeutic targets (molecular signaling pathways associated with cancer development) and 2) new cancer therapeutic candidates (drugs and agents that target molecular signaling pathways associated with cancer development). These may include new uses for existing drugs (drug re-purposing). This method was used to identify 1) genes and molecular signaling pathways associated with the development of cancer and 2) new drugs/agents that target those molecular signaling pathways and that could potentially lead to new therapeutics for ovarian cancer.

Also disclosed is an in silico method for individualized treatment of a subject with cancer that involves assaying an RNA sample from a tumor biopsy for differential gene expression in one or more molecular pathways, and using that information to select a suitable therapeutic regimine.

The details of one or more embodiments of the invention are set forth in the accompanying drawings and the description below. Other features, objects, and advantages of the invention will be apparent from the description and drawings, and from the claims.

DESCRIPTION OF DRAWINGS

FIG. 1 shows results for principal component analysis (PCA) of gene expressions in NOSE (open circles), primary pelvic (filled circles), and extrapelvic (triangles) samples. The first principal component (PC1) explains 35.4% of the variation, whereas the second (PC2) explains 6.3%.

FIGS. 2A-2C are Kaplan-Meier curves depicting the association between the TGF-WNT/cytoskeleton remodeling-pathway PCA score (using median PCA threshold) and overall survival from OVCA (GSE9891, survival information available for 218 of the 220 samples) (FIG. 2A), colon cancer (GSE17538, n=177) (FIG. 2B), and leukemia (TCGA database, n=182) (FIG. 2C). Log-rank test P values indicate significance.

FIG. 3 shows Kaplan-Meier curves depicting the association between the chemokines/cell adhesion pathway PCA score (using median PCA threshold) and overall survival from colon cancer (GSE17538, n=177). Log-rank test P values indicate significance.

FIGS. 4A and 4B are Kaplan-Meier curves depicting the association between the chemokines/cell adhesion pathway PCA score (using median PCA threshold) and overall survival from OVCA (MCC dataset, n=142) (FIG. 4A) and colon cancer (GSE17538, n=177) (FIG. 4B). Log-rank test P values indicate significance.

FIG. 5 shows HeyA8 cells treated with 25 mM and 50 mM artesunate (ART) were impaired in their ability to fill in the gap of a scratch test. In contrast, cells cultured in the presence of DMSO vehicle completely closed the gap within 2 days.

FIGS. 6A to 6C are maps of the TGF-WNT/cytoskeleton remodeling pathway (FIG. 6A), chemokines/cell adhesion pathway (FIG. 6B), and histamine signaling/immune response pathway (FIG. 6C). Thermometers indicate direction change (upward or downward) in expression of genes associated with extrapelvic implant samples.

FIG. 7 is a flow chart depicting an embodiment of an in silico method to identify therapeutic agents to treat cancer.

FIG. 8 is a flow chart depicting an embodiment of an in silico method for selecting a cancer treatment regimen for a subject.

DETAILED DESCRIPTION

Currently, the management of advanced-stage ovarian cancer (OVCA) includes cytoreductive surgery (debulking) followed by platinum-based chemotherapy. Approximately 70% of patients will demonstrate a complete clinical response to this primary therapeutic approach, however, the majority of these complete responders will eventually develop platinum-resistant, progressive or recurrent disease. Once platinum-resistance has developed, few active therapeutic options exist and patient survival is generally short-lived. These dismal statistics reflect in-part, an incomplete understanding of the root causes of ovary carcinogenesis and a lack of targeted agents that specifically attack the molecular basis of disease development.

Disclosed is an in silico method to identify molecular signaling pathways that influence cancer development, as well as to identify therapeutic compounds with activity against them. The method involves evaluating gene expression datasets to identify genes differentially expressed in cancer. For example, the method can involve identifying genes and represented pathways whose expression is increased or decreased in cancer by at least 50%, by at least 100%, or by at least 200%. The method can further involve identifying pathways represented by differentially expressed genes.

In some embodiments, the cancer is ovarian cancer (OVCA). However, the disclosed method may be used to identify molecular signaling pathways and drug candidates for any cancer type or subtype. A representative but non-limiting list of cancers include lymphoma, B cell lymphoma, T cell lymphoma, mycosis fungoides, Hodgkin's Disease, myeloid leukemia, bladder cancer, brain cancer, nervous system cancer, head and neck cancer, squamous cell carcinoma of head and neck, kidney cancer, lung cancers such as small cell lung cancer and non-small cell lung cancer, neuroblastoma/glioblastoma, ovarian cancer, pancreatic cancer, prostate cancer, skin cancer, liver cancer, melanoma, squamous cell carcinomas of the mouth, throat, larynx, and lung, colon cancer, cervical cancer, cervical carcinoma, breast cancer, epithelial cancer, renal cancer, genitourinary cancer, pulmonary cancer, esophageal carcinoma, head and neck carcinoma, large bowel cancer, hematopoietic cancers (e.g., leukemia); testicular cancer; rectal cancers, prostatic cancer, and pancreatic cancer.

In some cases, the method involves identifying genes and represented pathways within the genomic datasets that have a False Discovery Rate (FDR) less than 0.1, less than 0.05, or less than 0.01. Instead of controlling the chance of any false positives (as Bonferroni or random field methods do), FDR controls the expected proportion of false positives among suprathreshold voxels. An FDR threshold is determined from the observed p-value distribution, and hence is adaptive to the amount of signal in the data.

The method can further involve evaluating the differentially expressed pathways for associations with survival as an indication of biological relevance. The method can involve assaying a biological sample, such as a tumor biopsy, from the subject for gene expression levels, comparing these levels to control values to identify differentially expressed genes, identifying molecular pathways represented by the differentially expressed genes, evaluating the molecular pathways for associations with cancer survival as an indication of biological relevance, and identifying agents or drugs that have activity against the pathways associated with cancer survival.

In some embodiments, gene expression levels are determined using a gene expression microarray. Gene expression microarrays provide a snapshot of all the transcriptional activity in a biological sample. Unlike most traditional molecular biology tools, which generally allow the study of a single gene or a small set of genes, microarrays facilitate the discovery of totally novel and unexpected functional roles of genes. Non-limiting examples of gene expression microarrays include those produced by Affymetrix, Agilent, and Nimblegen. Affymetrix microarrays are composed of spots of 25-bp probes. A target sequence is associated with a “probe-set,” typically 11-16 probes whose signal is integrated to produce a single intensity. The sample is labeled by incorporation of biotin-labeled nucleotides, and a dedicated fluidics system washes the hybridized sample. Nimblegen and Agilent use different array synthesis methods that can create longer probes (up to ˜60 bp), and labeling is by cy3,5 fluores, which are also used to label cDNA arrays.

A wide range of methods to adjust for testing multiple samples to identify differential gene expression are available. Many rely on the assumption that the tests are independent. However, the preferred approach for microarray analysis is to control the “false-discovery rate” (FDR), the probability that any particular significant finding is a false-positive. To better account for the dependencies within the data, multiple testing adjustment using “permutation-based” methods can be used, which estimate the null distribution by permuting the actual data. If that is not feasible, the Benjamini-Hochberg step-down method offers a reasonable combination of statistical rigor and power for microarray analysis. As an example, the BioConductor software package or the GenePattern analysis pipeline software can be used to identify differential expression. Users of a multtest package can choose among several parametric methods (which make assumptions about the normality of the data), including the Welch t-test, paired t-test, or ANOVA. All of these look for differences in the average expression level between groups. Since assumptions about normality are often inappropriate, the reported p-values are more appropriately used as a guide to prioritizing the genes, not as accurate probabilities, even after adjusting for multiple testing.

Molecular pathways represented by the differentially expressed genes can be identified using databases of protein interactions and metabolic and signaling pathways. Examples of suitable databases include Ariadne Genomics' PathwayStudio®, BIOBASE's The ExPlain™ Analysis System, GeneGo's MetaCore™, Genomatix′ BiblioSphere Pathway Edition, and Ingenuity Pathways Analysis (IPA).

Multivariate statistical analysis can then be used to summate the expression of one or more molecular pathways into a single numeric value. For example, the method can involve the use of multivariate regression analysis (e.g., determined by linear regression) or principal component analysis (PCA) to generate a single numeric value for each molecular pathway. PCA is a multivariate technique that analyzes a data table in which observations are described by several inter-correlated quantitative dependent variables. Its goal is to extract the important information from the table, to represent it as a set of new orthogonal variables called principal components, and to display the pattern of similarity of the observations and of the variables as points in maps. Pathways with expression scores associated with 2 or more survival datasets can then evaluated in vitro.

The method can further involve in silico analysis to identify agents or drugs that have activity against the differentially expressed pathways associated with survival. For example, pathway scores and agent/drug sensitivity/activity scores can be compared, e.g., by Pearson's correlation, to identify drugs that demonstrate activity that correlate with the expression of each of the specific differentially expressed pathways associated with survival.

For example, using four paired normal/cancer genomic datasets from a total of 58 normal ovarian surface epithelium (NOSE) specimens and 756 epithelial ovarian cancer samples genes and represented pathways associated with OVCA were first identified in each dataset. Pathways found common to at least 3 datasets meeting an FDR<0.05 (n=14) were evaluated for associations with survival as an indication of biologic relevance. To do this, the expression of each pathway was summated into a single numeric value using PCA modeling of all objects (probesets/genes) within the pathway as defined by GeneGO Metacore™ software, and evaluated within 5 independent OVCA survival datasets. Those pathways with expression scores associated with 2 or more survival datasets were then evaluated within the NCI60 cancer cell line panel, drug screening database for associations with GI50 values over 48,000 compounds.

In this manner, TGF-WNT/cytoskeleton remodeling pathway, WNT2 pathway, integrin pathway, chemokines/cell adhesion pathway, and histamine signaling/immune response pathway were found differentially associated with OVCA and had expression (PCA) scores that suggested a biologic relevance to overall survival from the disease. Of course, it may be an oversimplification to discuss these pathways or any others as separate entities as more and more research highlights the networking and interconnectedness of biologic processes. For instance, targeting integrins directly or indirectly may decrease the invasive potential of OVCA (Choi Y P, et al. Biochem Biophys Res Commun. 2012 Epub. Sep. 28, 2012; Lau M T, et al. Cancer Lett. 2012 320(2):198-204; Sawada K, et al. J Oncol. 2012 Epub. Dec. 25, 2011), and influence chemoresponse (Loessner D, et al. Gynecol Oncol. 2012 Epub. Sep. 8, 2012), the latter of which may be associated with a downstream modulation of TGF-beta activity (Tumbarello D A, et al. Mol Cancer. 2012 11:36). For example, Integrins, TGF/Wnt, and Wnt pathways are known to affect epithelial-mesenchymal transition (EMT) (Kiefel H, et al. Carcinogenesis. 2012 33(10):1919-29; Shah P P, et al. Oncogene. 2012 31(26):3124-35; Gil D, et al. Adv Enzyme Regul. 2011 51(1):195-207; Jing Y, et al. Cell Biosci. 2011 1:29; Borok Z. J Clin Invest. 2009 119(1):7-10; Mamuya F A, et al. J Cell Mol Med. 2012 16(3):445-55; Chen Y S, et al. Mol Cell Proteomics. 2011 10(2):M110 001131).

The expression of the Integrins, TGF/Wnt, and Wnt pathways correlated with NCI60 cell line GI50 values to 89, 446, and 42 agents, respectively (Bonferroni adjusted P<0.01). Five agents were correlated with Integrins, TGF/Wnt, and Wnt pathways, while 38 compounds were common between the TGF/Wnt and Wnt pathway associations. In theory, agents identified by this methodology should demonstrate a negative influence on OVCA cell growth and/or survival through the targeted inhibition of the associated pathway. As proof of principle for this methodology, two agents were selected to test for activity against a panel of OVCA cells; Dasatinib, uniquely associated with Integrins pathway expression, and Artesunate, uniquely associated with TGF/Wnt pathway expression. Dasatinib showed significant anti-proliferative activity against a panel of OVCA cells. Similar outcomes were observed for the anti-malarial drug, Artesunate, which the in silico analysis identified to be associated with TGF/Wnt pathway expression. Artesunate has been reported to disrupt Wnt signaling as well as decrease the transcriptional expression of TGF-beta (Wang Y, et al. Zhonghua Gan Zang Bing Za Zhi. 2012 20(4):294-9; Li L N, et al. Int J Cancer. 2007 121(6):1360-5; Wenisch C, et al. J Clin Immunol. 1995 15(2):69-73). Artesunate also showed anti-proliferative activity against OVCA cells.

Therefore, also disclosed is a method of treating ovarian cancer. The method can involve administering to the subject a composition that inhibits the TGF-WNT/cytoskeleton remodeling pathway, WNT2 pathway, integrin pathway, chemokines/cell adhesion pathway, histamine signaling/immune response pathway, or any combination thereof. In some cases, the composition inhibits all of these pathways. The composition can contain, for example, Dasatinib, which is an inhibitor of the integrin pathway. The composition can contain Artesunate, which is an inhibitor of the TGF/Wnt pathway. Other agents for use in the disclosed compositions and methods can be identified by the methods disclosed herein.

In general, candidate agents can be identified from large libraries of natural products or synthetic (or semi-synthetic) extracts or chemical libraries according to methods known in the art. Those skilled in the field of drug discovery and development will understand that the precise source of test extracts or compounds is not critical to the screening procedure(s) used.

Accordingly, virtually any number of chemical extracts or compounds can be screened using the exemplary methods described herein. Examples of such extracts or compounds include, but are not limited to, plant-, fungal-, prokaryotic- or animal-based extracts, fermentation broths, and synthetic compounds, as well as modification of existing compounds. Numerous methods are also available for generating random or directed synthesis (e.g., semi-synthesis or total synthesis) of any number of chemical compounds, including, but not limited to, saccharide-, lipid-, peptide-, and nucleic acid-based compounds. Synthetic compound libraries are commercially available, e.g., from purveyors of chemical libraries including but not limited to ChemBridge Corporation (16981 Via Tazon, Suite G, San Diego, Calif., 92127, USA, www.chembridge.com); ChemDiv (6605 Nancy Ridge Drive, San Diego, Calif. 92121, USA); Life Chemicals (1103 Orange Center Road, Orange, Conn. 06477); Maybridge (Trevillett, Tintagel, Cornwall PL34 OHW, UK)

Alternatively, libraries of natural compounds in the form of bacterial, fungal, plant, and animal extracts are commercially available from a number of sources, including 02H, (Cambridge, UK), MerLion Pharmaceuticals Pte Ltd (Singapore Science Park II, Singapore 117528) and Galapagos NV (Generaal De Wittelaan L11 A3, B-2800 Mechelen, Belgium).

In addition, natural and synthetically produced libraries are produced, if desired, according to methods known in the art, e.g., by standard extraction and fractionation methods or by standard synthetic methods in combination with solid phase organic synthesis, micro-wave synthesis and other rapid throughput methods known in the art to be amenable to making large numbers of compounds for screening purposes. Furthermore, if desired, any library or compound, including sample format and dissolution is readily modified and adjusted using standard chemical, physical, or biochemical methods.

When a crude extract is found to have a desired activity, further fractionation of the positive lead extract is necessary to isolate chemical constituents responsible for the observed effect. The same assays described herein for the detection of activities in mixtures of compounds can be used to purify the active component and to test derivatives thereof. Methods of fractionation and purification of such heterogeneous extracts are known in the art. If desired, compounds shown to be useful agents for treatment are chemically modified according to methods known in the art. Compounds identified as being of therapeutic value may be subsequently analyzed using in vitro cell based models and animal models for diseases or conditions, such as those disclosed herein.

Candidate agents encompass numerous chemical classes, but are most often organic molecules, e.g., small organic compounds having a molecular weight of more than 100 and less than about 2,500 Daltons. Candidate agents can include functional groups necessary for structural interaction with proteins, particularly hydrogen bonding, and typically include at least an amine, carbonyl, hydroxyl or carboxyl group, for example, at least two of the functional chemical groups. The candidate agents often contain cyclical carbon or heterocyclic structures and/or aromatic or polyaromatic structures substituted with one or more of the above functional groups.

In some embodiments, the candidate agents are proteins. In some aspects, the candidate agents are naturally occurring proteins or fragments of naturally occurring proteins. Thus, for example, cellular extracts containing proteins, or random or directed digests of proteinaceous cellular extracts, can be used. In this way libraries of procaryotic and eucaryotic proteins can be made for screening using the methods herein. The libraries can be bacterial, fungal, viral, and vertebrate proteins, and human proteins.

The term “subject” refers to any individual who is the target of administration or treatment. The subject can be a vertebrate, for example, a mammal. Thus, the subject can be a human or veterinary patient. The term “patient” refers to a subject under the treatment of a clinician, e.g., physician.

The term “sample from a subject” refers to a tissue (e.g., tissue biopsy), organ, cell (including a cell maintained in culture), cell lysate (or lysate fraction), biomolecule derived from a cell or cellular material (e.g. a polypeptide or nucleic acid), or body fluid from a subject.

The term “treatment” refers to the medical management of a patient with the intent to cure, ameliorate, stabilize, or prevent a disease, pathological condition, or disorder. This term includes active treatment, that is, treatment directed specifically toward the improvement of a disease, pathological condition, or disorder, and also includes causal treatment, that is, treatment directed toward removal of the cause of the associated disease, pathological condition, or disorder. In addition, this term includes palliative treatment, that is, treatment designed for the relief of symptoms rather than the curing of the disease, pathological condition, or disorder; preventative treatment, that is, treatment directed to minimizing or partially or completely inhibiting the development of the associated disease, pathological condition, or disorder; and supportive treatment, that is, treatment employed to supplement another specific therapy directed toward the improvement of the associated disease, pathological condition, or disorder.

The term “tumor” or “neoplasm” refers to an abnormal mass of tissue containing neoplastic cells. Neoplasms and tumors may be benign, premalignant, or malignant. The term “cancer” or “malignant neoplasm” refers to a cell that displays uncontrolled growth, invasion upon adjacent tissues, and often metastasis to other locations of the body. The term “metastasis” refers to the spread of malignant tumor cells from one organ or part to another non-adjacent organ or part. Cancer cells can “break away,” “leak,” or “spill” from a primary tumor, enter lymphatic and blood vessels, circulate through the bloodstream, and settle down to grow within normal tissues elsewhere in the body. When tumor cells metastasize, the new tumor is called a secondary or metastatic cancer or tumor.

EXAMPLES Example 1 Materials and Methods

Identification of Molecular Signaling Pathways Associated with OVCA Development:

To identify molecular signaling pathways associated with OVCA development, an in silico analysis of 4 paired normal/cancer genomic datasets from a total of 58 normal ovarian surface epithelium (NOSE) specimens and 756 epithelial ovarian cancer samples was performed. The four datasets included: 1) the Moffitt (MCC) dataset (Affymetrix U133Plus GeneChips), 28 NOSE versus 78 OVCA; 2) the Total Cancer Care (TCC)™ dataset (Affymetrix Custom GeneChip Arrays), 12 NOSE versus 57 OVCA; 3) the Cancer Genome Atlas (TCGA) dataset (Affymetrix U133A GeneChips, publicly available), 8 NOSE versus 568 OVCA; and 4) the MD Anderson (MDA) Dataset (Affymetrix U133Plus GeneChips; publicly available), 10 NOSE versus 53 OVCA.

The MCC and TCC datasets were subjected to RMA using the Affymetrix Expression Console. Genes with an False Discovery Rate (FDR)<1% and a fold change >2 were selected for further pathway analysis. These genes were uploaded to GeneGo Metacore systems biology analysis software. Pathways represented within genes differentially expressed between NOSE and OVCA were identified and compared between the 4 datasets for commonly represented pathways.

Identification of Associations Between Expression of Molecular Signaling Pathways and Overall Survival of Patients with OVCA:

For pathways that were identified as common in 3 or more of the datasets, Principal Component Analysis (PCA) was used to generate a score that summarized the overall expression of each pathway. In this way, selecting the first principal component (PC1), a single numeric score was generated for each pathway, which summarized its level of expression. Associations were then explored between pathway expression (using median PC1 score as the threshold to define high versus low pathway score) and overall survival in 5 datasets for which both gene expression and overall survival data were available, including 1) The Moffitt (MCC) dataset (Affymetrix U133Plus GeneChips), n=142 OVCAs; 2) the Total Cancer Care (TCC)™ dataset (Affymetrix Custom GeneChip Arrays), n=57 OVCAs; 3) the Cancer Genome Atlas (TCGA) dataset (Affymetrix U133A GeneChips, publicly available), n=492 OVCAs; 4) the MD Anderson (MDA) Dataset (Affymetrix U133Plus GeneChips; publicly available), n=53 OVCAs; and 5) the Australian (Aus) Dataset (Affymetrix U133Plus GeneChips, publicly available), n=218 OVCAs.

Identification of Agents and Drugs that Target Molecular Signaling Pathways Associated with the Development of and Overall Survival from OVCA:

Pathways associated with the development of OVCA (differentially expressed between NOSE and OVCA) that also demonstrated associations between expression (PCA score) and overall patient survival in >2/5 datasets were subjected to further in silico analysis in an effort to identify novel agents or drugs that may have activity against the pathway. For this analysis, the aim was to identify novel therapeutic approaches to OVCA, either using agents that have not previously been explored as cancer therapeutics or re-purposing existing drugs as OVCA therapeutic agents. To accomplish this, Affymetrix HG-U133A expression genomic data was downloaded for 60 human cancer cell lines (6 leukemia, 9 melanoma, 9 non-small cell lung, 7 colon, 6 central nervous system, 7 ovarian, 8 renal, 2 prostate, and 6 breast cancer cell lines) and also measures of sensitivity (GI50) for each of the 60 cancer cell lines to ˜48,000 agents from the NCI website. For each pathway and all 48,000 agents/drugs in 59 NCI60 cells, a Pearson's correlation analysis was performed between pathway score and agent/drug sensitivity/activity (measured by GI50). The Pearson's correlation was between each pathway PC1 score and GI50 for ˜48,000 agents/drugs. Analysis was conducted to identify which of the 48,000 drugs demonstrated activity that correlated with the expression of each of the specific pathways. In this way, for each of the molecular signaling pathways found to be associated with both 1) OVCA development (differentially expressed between NOSE and OVCA) and 2) patient survival from OVCA, a list of agents was identified that showed activity correlated with pathway expression (that is, drugs predicted to target each specific pathway).

Statistical Analyses:

For each of the four datasets, gene expression data was compared at a probe-set level between NOSE and OVCA using Student's t-test. P-values were adjusted using the FDR methodology. For correlation analyses, significance was evaluated statistically by Pearson's score, P value, and Bonferroni-corrected P value.

Cell Culture and Survival Assays:

Ovarian cancer cell lines were either obtained from the European Collection of Cell Cultures, Salisbury, England (A2780S), or were kind gifts from Dr. Patricia Kruk, Department of Pathology, College of Medicine, University of South Florida, Tampa, Fla., and Susan Murphy, PhD, Dept of OB/GYN, Division of GYN Oncology, Duke University, Durham, N.C. (HeyA8, OVCAR2, OVCAR8, and OVCA420). Cell lines were maintained in RPMI-1640 (Invitrogen; Carlsbad, Calif.) supplemented with 10% fetal bovine serum (Fisher Scientific; Pittsburgh, Pa.), 1% sodium pyruvate, 1% penicillin/streptomycin, and 1% nonessential amino acids (HyClone; Hudson, N.H.). Mycoplasma testing was performed every 6 months following manufacturer's protocol (Lonza, Rockland, Me.).

The MTS assay was used to assess viability of the OVCA cell lines. For the assays, 3-5×10⁴ cells in 100 μL were plated to each well of a 96-well plate and allowed to adhere overnight at 37° C. and 5% CO₂. The following day, cells were incubated with increasing concentrations of drug for 72 hours. Cell viability was analyzed using the CellTiter96® MTS assay kit (Promega, Madison, Wis.). Three replicate wells were used for each drug concentration, and an additional three control wells received a diluent control without drug. After drug incubation, the optical density of each well was read at 490 nm using a SpectraMax 190 microplate reader (Molecular Devices Inc., Sunnyvale, Calif.). Percent cell survival was expressed as (control-treated)/(control-blank)×100. All experiments were performed three times, or the minimum number of times to ensure reproducibility and accuracy of the results.

Results

Identification of Molecular Signaling Pathways Associated with OVCA Development

In the in silico analysis of 4 paired normal/cancer genomic datasets from a total of 58 normal ovarian surface epithelium (NOSE) specimens and 756 epithelial ovarian cancer samples, the following numbers of differentially expressed genes (FDR<1%, fold-change >2) and represented pathways (FDR<5%) were identified: 923 genes in the Moffitt Cancer Center (MCC) dataset (506 upregulated, 417 downregulated), 2,942 genes in the Total Cancer Care (TCC) dataset (2,236 upregulated, 706 downregulated), 368 genes in The Cancer Genome Atlas (TCGA) dataset (117 upregulated, 251 downregulated), and 1,353 genes in the MD Anderson (MDA) dataset (231 upregulated, 1,122 downregulated) (Table 1). The following number of represented pathways (FDR<5%) were also identified: 19 in the MCC dataset, 35 in the TCC dataset, 18 pathways in the TCGA dataset, and 41 in the MDA dataset (Table 1).

TABLE 1 Genes and pathways associated with the development of OVCA. # # # Total # Sig. # OVCA Up Down Sig. Represented Dataset NOSE Samples Genes Genes Genes Pathways MCC 28 78 506 417 923 19 (U133PLUS) TCC 12 57 2236 706 2942 35 (HuRSTA) TCGA 8 568 117 251 368 18 (U133A) MDA 10 53 231 1122 1353 41 (U133PLUS) Gene cutoff: FDR < 0.01, fold change > 2 Pathway cutoff: FDR < 0.05

Of the pathways identified, 4 pathways were common to all 4 datasets, 28 pathways were common to 3, and 66 pathways were common to two datasets (Table 6). We found 181 pathways that were uniquely represented in one dataset only. The 4 pathways that were identified to be common in all 4 datasets were the following: 1) Cytoskeleton remodeling_TGF, WNT and cytoskeletal remodeling, 2) Immune response_Alternative complement pathway, 3) Immune response_MIF—the neuroendocrine-macrophage connector, and 4) Integrins (Table 2). A list of these pathways can be found in Table 2 along with the number of genes (objects) found differentially expressed in cancer belonging to that pathway over the total number of objects within that pathway, and the represented P-value.

TABLE 2 Common biologic pathways associated with OVCA development in all used databases. Cytoskeleton remodeling_TGF, Immune response_ WNT and Alternative Pathway cytoskeletal remodeling complement pathway Database MCC TCC TCGA MDA MCC TCC TCGA MDA # Objects 7/111 16/111 5/111 10/111 4/39 16/39 3/39 10/39 P-Value 0.033 0.009 0.034 0.008 0.022 <0.001 0.025 <0.001 FDR < 0.05? No No No No No Yes No Yes Immune response_MIF- the neuroendocrine- Pathway macrophage connector Integrins Database MCC TCC TCGA MDA MCC TCC TCGA MDA # Objects 5/46  8/46 3/46  7/46 3/22  5/22 2/22  3/22 P-Value 0.008 0.021 0.038 0.001 0.022  0.022 0.049  0.046 FDR < 0.05? No No No Yes No No No No MCC: Moffitt Cancer Center TCC: Total Cancer Care Protocol TCGA: Thel Cancer Genome Atlas MDA: MD Anderson

Out of the 28 pathways found common in 3 datasets, 10 pathways showed an FDR<0.05, including: 1) Cell cycle_The metaphase checkpoint, 2) Cell cycle_Spindle assembly and chromosome separation, 3) Cell cycle_Role of APC in cell cycle regulation, 4) Cell cycle_Chromosome condensation in prometaphase, 5) Cell cycle_Initiation of mitosis, 6) Cell cycle_Nucleocytoplasmic transport of CDK/Cyclins, 7) Reproduction_Progesterone-mediated oocyte maturation, 8) Cell cycle_Role of Nek in cell cycle regulation, 9) Cell adhesion_Tight junctions, and 10) Development_WNT signaling pathway, Part 2.

Identification of Associations Between Expression of Molecular Signaling Pathways and Overall Survival of Patients with OVCA

To analyze associations between pathway expression and patient overall survival, the PCA methodology was used to derive a numeric score that summarized the overall expression of each pathway. The first principal component (PC1), which contains the highest variance, was used to define high versus low pathway score. Using the median PC1 as a threshold, each of the 14 pathways (pathways common to ≧3 datasets with FDR<0.05) was tested for an association with overall survival in 5 independent OVCA datasets (Table 3). Only pathways associated with survival in more than one OVCA dataset were considered further. This analysis indicated that overall survival from OVCA was associated with the expression of TGF/WNT, Integrins, and WNT2 pathways. Expression of the TGF/WNT pathway was associated with survival in two datasets (MCC, P<0.01 and Aus, P<0.01). Expression of the Integrins pathway was associated with survival in three datasets (MCC, P<0.001, Aus, P=0.02; and TCC™, P=0.05). WNT2 was associated with survival in two datasets (MCC, P<0.01; and TCC™, P<0.01) (Table 3). Genes included in the PC1 signature scores for the Integrins, TGF/WNT, and WNT2 pathways are listed in Table 4.

TABLE 3 The association of pathway expression scores, as determined by PCA modeling, with survival from OVCA. Median PCA score was used as a threshold. p-values Pathway Name Abbreviation MCC MDA AUS TCC TCGA Cytoskeleton remodeling_TGF, TGF.WNT 0.0099 0.1247 0.0055 0.4695 0.9162 WNT and cytoskeletal remodeling Immune response_Alternative Immune 0.3255 0.6733 0.6925 0.5714 0.2034 complement pathway Immune response_MIF - the MIF 0.0016 0.8244 0.3228 0.9348 0.1161 neuroendocrine-macrophage connector Integrins Integrins 4.00E−04 0.9618 0.0221 0.0457 0.723 Cell cycle_The metaphase metaphase 0.7817 0.4034 0.8891 0.264 0.9152 checkpoint Cell cycle_Spindle assembly and Spindle 0.3587 0.5336 0.6782 0.2669 0.6367 chromosome separation Cell cycle_Role of APC in cell APC 0.2925 0.7035 0.8763 0.3237 0.6887 cycle regulation Cell cycle_Chromosome prometaphase 0.123 0.2978 0.9533 0.1674 0.461 condensation in prometaphase Cell cycle_Initiation of mitosis mitosis 0.0779 0.9422 0.8708 0.0808 0.2365 Cell cycle_Nucleocytoplasmic CDK 0.515 0.5642 0.8876 0.6047 0.5741 transport of CDK/Cyclins Reproduction_Progesterone- oocyte 0.0059 0.7217 0.1051 0.5166 0.7599 mediated oocyte maturation Cell cycle_Role of Nek in cell Nek 0.6154 0.9161 0.8622 0.1557 0.7758 cycle regulation Cell adhesion_Tight junctions Tight 0.0249 0.9733 0.0631 0.8872 0.9205 Development_WNT signaling WNT2 0.002 0.4174 0.1594 0.0081 0.343 pathway. Part 2

TABLE 4 Genes used for PCA modeling from the Integrins, TGF/Wnt, and Wnt pathways. TGF-WNT WNT2 Integrins ACTA1 APC ANGPT1 ACTA2 AXIN1 ANGPT2 ACTB AXIN2 EGFR ACTC1 BMP4 F11R ACTG1 SMARCA4 FGF1 ACTG2 BCL9 FIGF ACTN1 CTNNB1 FLT1 ACTN2 CREBBP ITGA1 ACTN3 CD44 ITGA3 ACTN4 CBY1 ITGA5 ACTR2 CSNK1E ITGA9 ACTR3 CSNK2A1 ITGAV ACTR3B CSNK2A2 ITGB1 AKT1 CLDN1 ITGB3 AKT2 CCND1 ITGB6 AKT3 DAB2 ITGB8 ARPC1A DKK1 KDR ARPC1B DVL1 NGF ARPC2 DVL2 PRKCA ARPC3 DVL3 PRKCB ARPC4 CDH1 PRKCD ARPC5 ENC1 PRKCE AXIN1 FRAT1 PRKCG AXIN2 FOSL1 PRKCH BCAR1 FZD1 PRKCI CASP9 FZD10 PRKCQ CAV1 FZD2 PRKCZ CCND1 FZD3 PRKD1 CDC42 FZD4 PRKD2 CDKN1A FZD5 PRKD3 CDKN2B FZD6 PTK2 CFL1 FZD7 SEMA7A CFL2 FZD8 SRC CHUK FZD9 VEGFA COL4A1 GSK3B VEGFC COL4A2 TCF4 COL4A3 LRP5 COL4A4 LEF1 COL4A5 MESDC2 COL4A6 MMP26 CRK MMP7 CSNK2A1 NLK CSNK2A2 NRCAM CSNK2B REST CTNNB1 PPM1A DOCK1 PPARD DSTN PYGO1 DVL1 PYGO2 DVL2 GAST DVL3 RUVBL1 EIF4E RUVBL2 EIF4EBP1 RHOA FN1 SNAI2 FOXO3 SNAI1 FRAT1 BIRC5 FZD1 TAB1 FZD10 MAP3K7 FZD2 TCF7L2 FZD3 TCF7 FZD4 TCF7L1 FZD5 VEGFA FZD6 VIM FZD7 WIF1 FZD8 WNT1 FZD9 WNT10A GRB2 WNT10B GSK3B WNT11 HRAS WNT16 ILK WNT2 JUN WNT2B KDR WNT3 LAMA1 WNT3A LAMB1 WNT4 LAMC1 WNT5A LEF1 WNT5B LIMK1 WNT6 LIMK2 WNT7A LRP5 WNT7B MAP2K1 WNT8A MAP2K2 WNT8B MAP2K3 WNT9A MAP3K11 WNT9B MAP3K7 JUN MAPK1 MYC MAPK11 MAPK12 MAPK13 MAPK14 MAPK3 MDM2 MKNK1 MMP13 MMP7 MTOR MYC MYL1 MYL12A MYL12B MYL2 MYL3 MYL4 MYL5 MYL6 MYL6B MYL7 MYL9 MYLK MYLK2 MYLK3 MYLPF NCL NLK PAK1 PIK3CA PIK3CB PIK3CD PIK3R1 PIK3R2 PIK3R3 PLAT PLAU PLAUR PLG PPARD PPP1CB PPP1R12A PTK2 PXN RAC1 RAF1 RHEB RHOA ROCK1 ROCK2 RPS6KA5 SERPINE1 SERPING1 SHC1 SMAD2 SMAD3 SOS1 SOS2 SP1 SRC TAB1 TCF7 TCF7L1 TCF7L2 TGFB1 TGFBR1 TGFBR2 TLN1 TLN2 TP53 TSC2 VAV1 VCL VEGFA VTN WASL WIF1 WNT1 WNT10A WNT10B WNT11 WNT16 WNT2 WNT2B WNT3 WNT3A WNT4 WNT5A WNT5B WNT6 WNT7A WNT7B WNT8A WNT8B WNT9A WNT9B XIAP ZFYVE9

Identification of Compounds that Target Molecular Signaling Pathways Associated with the Development of and Overall Survival from OVCA

In an effort to identify novel therapeutic approaches for the treatment of OVCA, either using agents not previously explored as cancer therapeutics or by re-purposing existing drugs as OVCA therapeutic agents, compounds were identified with in vitro activity that correlated with pathway expression. Pathways that were associated with the development of OVCA (differentially expressed between NOSE and OVCA) and that demonstrated associations between expression (PCA score) and overall patient survival in more than one OVCA dataset were correlated with in-vitro sensitivity of the NCI60 cell line panel to 48,000 compounds. Pearson's correlation indicated that in-vitro expression of the Integrins pathway (quantified by PC1 score) was associated with NCI60 cell line sensitivity (quantified by GI50) to 89 agents (P<0.01, Bonferroni adjusted), whereas the WNT2 pathway PC1 score was associated with sensitivity to 42 agents (P<0.01, Bonferroni adjusted), and the TGF/WNT pathway PC1 score was associated with sensitivity to 446 agents (P<0.01, Bonferroni adjusted) (Tables 7-9).

Identified Compounds Decrease OVCA Cell Proliferation

The cytotoxic effects of continuous exposure to dasatinib and artesunate were assessed for five OVCA cell lines at 72 hours using the MTS assay (Table 5). The mean IC₅₀ of Dasatinib was 0.577 uM (log 10; −0.30486 uM) with a range of 0.214 uM to 0.953 uM (log 10; −0.02085 uM to −0.6685 uM). The median IC₅₀ of artesunate was 7.13 uM (log 10; 0.6321 uM) with a range of 1.23 uM to 19.32 uM (log 10; 0.0882 uM to 1.286 uM).

TABLE 5 Sensitivity of OVCA cell lines to Dasatinib and Artesunate as determined by MTS cell proliferation assays. A2780S OVCA420 OVCA2 OVCA8 HEYA8 Dasatinib: Log₁₀ IC₅₀ −0.03735 −0.3655 −0.02085 −0.4321 −0.6685 SEM 0.03997 0.1225 0.1337 0.05971 0.07254 Artesunate: Log₁₀ IC₅₀ 0.0882 1.286 0.1173 0.7705 0.8985 SEM 0.0564 0.06618 0.02667 0.05188 0.07381

TABLE 6 Pathways common to all datasets FDR Pathway Name <0.05 p-value ratio dataset common Cytoskeleton remodeling_TGF, WNT and no 9.05E−03 16/111 tcc 4 cytoskeletal remodeling Cytoskeleton remodeling_TGF, WNT and no 3.39E−02  5/111 tcga 4 cytoskeletal remodeling Cytoskeleton remodeling_TGF, WNT and no 8.06E−03 10/111 mda 4 cytoskeletal remodeling Cytoskeleton remodeling_TGF, WNT and no 3.33E−02  7/111 mcc 4 cytoskeletal remodeling Immune response_Alternative complement yes 6.99E−09 16/39  tcc 4 pathway Immune response_Alternative complement no 2.49E−02 3/39 tcga 4 pathway Immune response_Alternative complement yes 1.05E−06 10/39  mda 4 pathway Immune response_Alternative complement no 2.17E−02 4/39 mcc 4 pathway Immune response_MIF - the no 2.07E−02 8/46 tcc 4 neuroendocrine-macrophage connector Immune response_MIF - the no 3.81E−02 3/46 tcga 4 neuroendocrine-macrophage connector Immune response_MIF - the yes 1.40E−03 7/46 mda 4 neuroendocrine-macrophage connector Immune response_MIF - the no 8.30E−03 5/46 mcc 4 neuroendocrine-macrophage connector Integrins no 2.18E−02 5/22 tcc 4 Integrins no 4.87E−02 2/22 tcga 4 Integrins no 4.63E−02 3/22 mda 4 Integrins no 2.16E−02 3/22 mcc 4 Apoptosis and survival_BAD no 4.58E−03 4/42 tcga 3 phosphorylation Apoptosis and survival_BAD yes 8.00E−04 7/42 mda 3 phosphorylation Apoptosis and survival_BAD no 5.63E−03 5/42 mcc 3 phosphorylation Apoptosis and survival_Role of IAP- no 1.34E−02 3/31 tcga 3 proteins in apoptosis Apoptosis and survival_Role of IAP- no 2.66E−02 4/31 mda 3 proteins in apoptosis Apoptosis and survival_Role of IAP- yes 1.69E−04 6/31 mcc 3 proteins in apoptosis Cell adhesion_Endothelial cell contacts by yes 1.15E−06 11/26  tcc 3 junctional mechanisms Cell adhesion_Endothelial cell contacts by no 1.46E−02 4/26 mda 3 junctional mechanisms Cell adhesion_Endothelial cell contacts by yes 5.94E−05 6/26 mcc 3 junctional mechanisms Cell adhesion_Plasmin signaling no 3.88E−03 8/35 tcc 3 Cell adhesion_Plasmin signaling yes 1.63E−03 6/35 mda 3 Cell adhesion_Plasmin signaling no 2.51E−03 5/35 mcc 3 Cell adhesion_Tight junctions yes 2.39E−04 10/36  tcc 3 Cell adhesion_Tight junctions yes 1.90E−03 6/36 mda 3 Cell adhesion_Tight junctions yes 3.99E−04 6/36 mcc 3 Cell cycle_Cell cycle (generic schema) yes 1.71E−05 5/21 tcga 3 Cell cycle_Cell cycle (generic schema) no 6.76E−03 4/21 mda 3 Cell cycle_Cell cycle (generic schema) yes 1.57E−05 6/21 mcc 3 Cell cycle_Chromosome condensation in yes 2.71E−13 10/21  tcga 3 prometaphase Cell cycle_Chromosome condensation in yes 4.40E−07 8/21 mda 3 prometaphase Cell cycle_Chromosome condensation in yes 4.39E−08 8/21 mcc 3 prometaphase Cell cycle_Initiation of mitosis yes 2.23E−06 6/25 tcga 3 Cell cycle_Initiation of mitosis yes 2.06E−06 8/25 mda 3 Cell cycle_Initiation of mitosis yes 3.46E−06 7/25 mcc 3 Cell cycle_Nucleocytoplasmic transport of yes 4.37E−08 6/14 tcga 3 CDK/Cyclins Cell cycle_Nucleocytoplasmic transport of yes 1.04E−04 5/14 mda 3 CDK/Cyclins Cell cycle_Nucleocytoplasmic transport of yes 3.21E−08 7/14 mcc 3 CDK/Cyclins Cell cycle_Regulation of G1/S transition yes 2.92E−05 6/38 tcga 3 (part 1) Cell cycle_Regulation of G1/S transition yes 2.52E−03 6/38 mda 3 (part 1) Cell cycle_Regulation of G1/S transition no 3.63E−03 5/38 mcc 3 (part 1) Cell cycle_Regulation of G1/S transition yes 7.47E−04 4/26 tcga 3 (part 2) Cell cycle_Regulation of G1/S transition no 1.46E−02 4/26 mda 3 (part 2) Cell cycle_Regulation of G1/S transition no 5.21E−03 4/26 mcc 3 (part 2) Cell cycle_Role of APC in cell cycle yes 1.30E−12 11/32  tcga 3 regulation Cell cycle_Role of APC in cell cycle yes 9.96E−09 11/32  mda 3 regulation Cell cycle_Role of APC in cell cycle yes 1.26E−07 9/32 mcc 3 regulation Cell cycle_Role of Nek in cell cycle yes 1.21E−09 9/32 tcga 3 regulation Cell cycle_Role of Nek in cell cycle yes 1.59E−05 8/32 mda 3 regulation Cell cycle_Role of Nek in cell cycle yes 1.67E−03 5/32 mcc 3 regulation Cell cycle_Sister chromatid cohesion yes 3.84E−04 4/22 tcga 3 Cell cycle_Sister chromatid cohesion no 8.03E−03 4/22 mda 3 Cell cycle_Sister chromatid cohesion no 2.16E−02 3/22 mcc 3 Cell cycle_Spindle assembly and yes 1.29E−15 13/33  tcga 3 chromosome separation Cell cycle_Spindle assembly and yes 1.45E−08 11/33  mda 3 chromosome separation Cell cycle_Spindle assembly and yes 1.10E−08 10/33  mcc 3 chromosome separation Cell cycle_The metaphase checkpoint yes 1.80E−13 12/36  tcga 3 Cell cycle_The metaphase checkpoint yes 3.13E−09 12/36  mda 3 Cell cycle_The metaphase checkpoint yes 1.79E−09 11/36  mcc 3 Cell cycle_Transition and termination of yes 9.97E−04 4/28 tcga 3 DNA replication Cell cycle_Transition and termination of no 1.89E−02 4/28 mda 3 DNA replication Cell cycle_Transition and termination of yes 9.28E−05 6/28 mcc 3 DNA replication Cytoskeleton remodeling_Keratin filaments yes 7.33E−06 12/36  tcc 3 Cytoskeleton remodeling_Keratin filaments no 4.32E−02 4/36 mda 3 Cytoskeleton remodeling_Keratin filaments yes 3.85E−07 9/36 mcc 3 Development_EPO-induced PI3K/AKT no 4.08E−02 7/43 tcc 3 pathway and Ca(2+) influx Development_EPO-induced PI3K/AKT no 3.20E−02 3/43 tcga 3 pathway and Ca(2+) influx Development_EPO-induced PI3K/AKT no 2.99E−02 4/43 mcc 3 pathway and Ca(2+) influx Development_Regulation of epithelial-to- no 2.10E−02 10/64  tcc 3 mesenchymal transition (EMT) Development_Regulation of epithelial-to- yes 8.65E−10 16/64  mda 3 mesenchymal transition (EMT) Development_Regulation of epithelial-to- no 8.11E−03 6/64 mcc 3 mesenchymal transition (EMT) Development_TGF-beta-dependent no 4.53E−02 6/35 tcc 3 induction of EMT via SMADs Development_TGF-beta-dependent yes 3.46E−07 10/35  mda 3 induction of EMT via SMADs Development_TGF-beta-dependent no 2.51E−03 5/35 mcc 3 induction of EMT via SMADs Development_WNT signaling pathway. Part 2 yes 1.73E−03 11/53  tcc 3 Development_WNT signaling pathway. Part 2 yes 6.81E−04 8/53 mda 3 Development_WNT signaling pathway. Part 2 yes 5.76E−04 7/53 mcc 3 G-protein signaling_Regulation of CDC42 no 3.51E−02 6/33 tcc 3 activity G-protein signaling_Regulation of CDC42 yes 1.87E−03 4/33 tcga 3 activity G-protein signaling_Regulation of CDC42 yes 1.18E−03 6/33 mda 3 activity Histamine metabolism yes 1.14E−03 4/29 tcga 3 Histamine metabolism no 2.13E−02 4/29 mda 3 Histamine metabolism no 4.45E−02 3/29 mcc 3 PGE2 pathways in cancer yes 6.78E−04 12/55  tcc 3 PGE2 pathways in cancer no 1.57E−02 6/55 mda 3 PGE2 pathways in cancer yes 1.17E−04 8/55 mcc 3 Reproduction_Progesterone-mediated yes 4.32E−04 5/40 tcga 3 oocyte maturation Reproduction_Progesterone-mediated yes 1.18E−05 9/40 mda 3 oocyte maturation Reproduction_Progesterone-mediated yes 7.17E−04 6/40 mcc 3 oocyte maturation Retinol metabolism/Rodent version yes 2.01E−03 13/70  tcc 3 Retinol metabolism/Rodent version no 2.65E−02 4/70 tcga 3 Retinol metabolism/Rodent version no 4.49E−02 6/70 mda 3 Signal transduction_PKA signaling no 1.32E−02 9/51 tcc 3 Signal transduction_PKA signaling no 3.98E−02 5/51 mda 3 Signal transduction_PKA signaling no 1.27E−02 5/51 mcc 3 Apoptosis and survival_HTR1A signaling no 3.26E−02 8/50 tcc 2 Apoptosis and survival_HTR1A signaling no 1.00E−02 6/50 mda 2 Apoptosis and survival_p53-dependent yes 1.14E−03 4/29 tcga 2 apoptosis Apoptosis and survival_p53-dependent yes 1.05E−03 5/29 mcc 2 apoptosis Apoptosis and survival_Role of CDK5 in no 1.73E−02 3/34 tcga 2 neuronal death and survival Apoptosis and survival_Role of CDK5 in no 2.20E−03 5/34 mcc 2 neuronal death and survival Cell adhesion_Cadherin-mediated cell yes 4.72E−04 8/26 tcc 2 adhesion Cell adhesion_Cadherin-mediated cell no 3.37E−02 3/26 mcc 2 adhesion Cell adhesion_Chemokines and adhesion yes 4.45E−04 18/100 tcc 2 Cell adhesion_Chemokines and adhesion yes 3.11E−04 12/100 mda 2 Cell adhesion_ECM remodeling yes 9.49E−05 13/52  tcc 2 Cell adhesion_ECM remodeling yes 2.40E−06 11/52  mda 2 Cell adhesion_Ephrin signaling no 5.77E−03 9/45 tcc 2 Cell adhesion_Ephrin signaling yes 1.22E−03 7/45 mda 2 Cell adhesion_Histamine H1 receptor no 5.77E−03 9/45 tcc 2 signaling in the interruption of cell barrier integrity Cell adhesion_Histamine H1 receptor no 3.46E−02 4/45 mcc 2 signaling in the interruption of cell barrier integrity Cell adhesion_Role of CDK5 in cell no 3.01E−03 4/9  tcc 2 adhesion Cell adhesion_Role of CDK5 in cell no 2.39E−02 2/9  mcc 2 adhesion Cell cycle_Role of 14-3-3 proteins in cell no 5.11E−03 3/22 tcga 2 cycle regulation Cell cycle_Role of 14-3-3 proteins in cell no 2.16E−02 3/22 mcc 2 cycle regulation Cell cycle_Role of SCF complex in cell no 1.12E−02 3/29 tcga 2 cycle regulation Cell cycle_Role of SCF complex in cell no 7.76E−03 4/29 mcc 2 cycle regulation Cell cycle_Start of DNA replication in early no 1.46E−02 3/32 tcga 2 S phase Cell cycle_Start of DNA replication in early no 2.96E−02 4/32 mda 2 S phase CFTR-dependent regulation of ion channels no 1.60E−02 8/44 tcc 2 in Airway Epithelium (norm and CF) CFTR-dependent regulation of ion channels no 6.88E−03 5/44 mcc 2 in Airway Epithelium (norm and CF) Chemotaxis_Inhibitory action of lipoxins on no 4.93E−02 3/51 tcga 2 IL-8- and Leukotriene B4-induced neutrophil migration Chemotaxis_Inhibitory action of lipoxins on no 3.98E−02 5/51 mda 2 IL-8- and Leukotriene B4-induced neutrophil migration Chemotaxis_Leukocyte chemotaxis yes 4.12E−04 15/75  tcc 2 Chemotaxis_Leukocyte chemotaxis no 3.31E−02 4/75 tcga 2 Cytoskeleton remodeling_Reverse signaling no 2.65E−02 6/31 tcc 2 by ephrin B Cytoskeleton remodeling_Reverse signaling no 2.66E−02 4/31 mda 2 by ephrin B Development_A1 receptor signaling no 4.43E−02 8/53 tcc 2 Development_A1 receptor signaling yes 6.81E−04 8/53 mda 2 Development_Angiotensin signaling via no 3.06E−02 6/32 tcc 2 STATs Development_Angiotensin signaling via no 2.96E−02 4/32 mda 2 STATs Development_Delta- and kappa-type opioid no 6.07E−03 6/23 tcc 2 receptors signaling via beta-arrestin Development_Delta- and kappa-type opioid no 9.44E−03 4/23 mda 2 receptors signaling via beta-arrestin Development_Hedgehog signaling yes 1.93E−03 10/46  tcc 2 Development_Hedgehog signaling yes 2.51E−04 8/46 mda 2 Development_Leptin signaling via no 3.66E−02 5/25 tcc 2 JAK/STAT and MAPK cascades Development_Leptin signaling via no 3.04E−02 3/25 mcc 2 JAK/STAT and MAPK cascades Development_MicroRNA-dependent no 5.01E−03 3/10 mda 2 inhibition of EMT Development_MicroRNA-dependent no 2.94E−02 2/10 mcc 2 inhibition of EMT Development_PEDF signaling no 4.46E−02 3/49 tcga 2 Development_PEDF signaling no 3.43E−02 5/49 mda 2 Development_PIP3 signaling in cardiac no 4.02E−02 3/47 tcga 2 myocytes Development_PIP3 signaling in cardiac no 3.98E−02 4/47 mcc 2 myocytes Development_Role of CDK5 in neuronal no 1.73E−02 3/34 tcga 2 development Development_Role of CDK5 in neuronal no 3.60E−02 4/34 mda 2 development Development_SSTR1 in regulation of cell no 1.94E−02 6/29 tcc 2 proliferation and migration Development_SSTR1 in regulation of cell no 4.45E−02 3/29 mcc 2 proliferation and migration Development_TGF-beta-dependent no 3.81E−02 3/46 tcga 2 induction of EMT via RhoA, PI3K and ILK. Development_TGF-beta-dependent yes 3.91E−05 9/46 mda 2 induction of EMT via RhoA, PI3K and ILK. Development_Thrombospondin-1 signaling no 1.89E−02 4/28 mda 2 Development_Thrombospondin-1 signaling no 4.07E−02 3/28 mcc 2 Development_VEGF signaling and no 3.20E−02 3/43 tcga 2 activation Development_VEGF signaling and no 4.77E−03 6/43 mda 2 activation Development_VEGF signaling via VEGFR2 - no 2.35E−02 12/84  tcc 2 generic cascades Development_VEGF signaling via VEGFR2 - no 4.71E−02 4/84 tcga 2 generic cascades DNA damage_ATM/ATR regulation of G2/ yes 7.47E−04 4/26 tcga 2 M checkpoint DNA damage_ATM/ATR regulation of G2/ no 5.21E−03 4/26 mcc 2 M checkpoint DNA damage_ATM/ATR regulation of yes 1.67E−03 4/32 tcga 2 G1/S checkpoint DNA damage_ATM/ATR regulation of no 1.10E−02 4/32 mcc 2 G1/S checkpoint DNA damage_Brca1 as a transcription no 1.23E−02 3/30 tcga 2 regulator DNA damage_Brca1 as a transcription yes 1.40E−04 6/30 mcc 2 regulator ENaC regulation in airways (normal and no 4.01E−02 8/52 tcc 2 CF) ENaC regulation in airways (normal and no 4.28E−02 5/52 mda 2 CF) G-protein signaling_G-Protein alpha-i yes 2.81E−03 5/27 mda 2 signaling cascades G-protein signaling_G-Protein alpha-s no 4.32E−02 4/36 mda 2 signaling cascades G-protein signaling_Proinsulin C-peptide no 9.78E−03 4/52 tcga 2 signaling G-protein signaling_Proinsulin C-peptide no 4.28E−02 5/52 mda 2 signaling G-protein signaling_Regulation of RAC1 no 2.01E−02 3/36 tcga 2 activity G-protein signaling_Regulation of RAC1 no 1.00E−02 5/36 mda 2 activity G-protein signaling_RhoA regulation yes 7.22E−04 9/34 tcc 2 pathway G-protein signaling_RhoA regulation no 3.60E−02 4/34 mda 2 pathway Immune response_CD28 signaling no 4.87E−02 8/54 tcc 2 Immune response_CD40 signaling no 8.92E−03 11/65  tcc 2 Immune response_Classical complement yes 4.74E−12 22/52  tcc 2 pathway Immune response_Classical complement yes 3.50E−09 14/52  mda 2 pathway Immune response_CXCR4 signaling via no 4.00E−02 6/34 tcc 2 second messenger Immune response_CXCR4 signaling via no 3.60E−02 4/34 mda 2 second messenger Immune response_IL-5 signalling no 4.54E−02 7/44 tcc 2 Immune response_IL-5 signalling no 3.40E−02 3/44 tcga 2 Immune response_Inflammasome in no 1.43E−02 7/35 tcc 2 inflammatory response Immune response_Inflammasome in no 3.95E−02 4/35 mda 2 inflammatory response Immune response_Lectin induced yes 1.00E−13 23/49  tcc 2 complement pathway Immune response_Lectin induced yes 1.49E−07 12/49  mda 2 complement pathway Immune response_MIF-JAB1 signaling no 6.56E−03 3/24 tcga 2 Immune response_MIF-JAB1 signaling no 2.73E−02 3/24 mcc 2 Immune response_Oncostatin M signaling no 1.66E−02 3/20 mcc 2 via JAK-Stat in human cells Immune response_Oncostatin M signaling no 1.24E−02 3/18 mcc 2 via JAK-Stat in mouse cells Immune response_PGE2 common pathways no 4.96E−03 10/52  tcc 2 Immune response_PGE2 common pathways yes 2.89E−03 7/52 mda 2 Immune response_PGE2 in immune and no 1.60E−02 8/44 tcc 2 neuroendocrine system interactions Immune response_PGE2 in immune and no 5.36E−03 6/44 mda 2 neuroendocrine system interactions Neurophysiological process_Corticoliberin no 3.70E−02 5/50 mda 2 signaling via CRHR1 Neurophysiological process_Corticoliberin no 4.82E−02 4/50 mcc 2 signaling via CRHR1 Neurophysiological process_Dopamine D2 no 4.25E−02 5/26 tcc 2 receptor transactivation of PDGFR in CNS Neurophysiological process_Dopamine D2 no 1.46E−02 4/26 mda 2 receptor transactivation of PDGFR in CNS Neurophysiological process_Netrin-1 in no 2.99E−03 9/41 tcc 2 regulation of axon guidance Neurophysiological process_Netrin-1 in no 3.75E−03 6/41 mda 2 regulation of axon guidance Neurophysiological process_PGE2-induced no 4.08E−02 7/43 tcc 2 pain processing Neurophysiological process_PGE2-induced no 2.07E−02 5/43 mda 2 pain processing Neurophysiological process_Receptor- no 5.77E−03 9/45 tcc 2 mediated axon growth repulsion Neurophysiological process_Receptor- no 2.48E−02 5/45 mda 2 mediated axon growth repulsion Proteolysis_Role of Parkin in the Ubiquitin- yes 1.62E−03 5/24 mda 2 Proteasomal Pathway Proteolysis_Role of Parkin in the Ubiquitin- no 2.73E−02 3/24 mcc 2 Proteasomal Pathway Pyruvate metabolism no 4.46E−02 3/49 tcga 2 Pyruvate metabolism no 4.53E−02 4/49 mcc 2 Retinol metabolism yes 3.54E−04 15/74  tcc 2 Retinol metabolism no 3.17E−02 4/74 tcga 2 Role of alpha-6/beta-4 integrins in yes 1.62E−03 10/45  tcc 2 carcinoma progression Role of alpha-6/beta-4 integrins in no 2.48E−02 5/45 mda 2 carcinoma progression Signal transduction_Activation of PKC via yes 1.47E−03 11/52  tcc 2 G-Protein coupled receptor Signal transduction_Activation of PKC via no 4.28E−02 5/52 mda 2 G-Protein coupled receptor Signal transduction_cAMP signaling no 2.21E−02 7/38 tcc 2 Signal transduction_cAMP signaling yes 4.25E−04 7/38 mda 2 Some pathways of EMT in cancer cells no 3.63E−02 8/51 tcc 2 Some pathways of EMT in cancer cells no 1.10E−02 6/51 mda 2 Transcription_Androgen Receptor nuclear no 1.82E−02 8/45 tcc 2 signaling Transcription_Androgen Receptor nuclear no 2.48E−02 5/45 mda 2 signaling Transcription_Ligand-dependent activation no 1.23E−02 3/30 tcga 2 of the ESR1/SP pathway Transcription_Ligand-dependent activation yes 1.23E−03 5/30 mcc 2 of the ESR1/SP pathway Transcription_P53 signaling pathway yes 2.07E−03 9/39 tcc 2 Transcription_P53 signaling pathway no 2.49E−02 3/39 tcga 2 Transcription_Role of heterochromatin no 4.87E−02 2/22 tcga 2 protein 1 (HP1) family in transcriptional silencing Transcription_Role of heterochromatin no 4.63E−02 3/22 mda 2 protein 1 (HP1) family in transcriptional silencing Translation_Non-genomic (rapid) action of yes 2.50E−03 9/40 tcc 2 Androgen Receptor Translation_Non-genomic (rapid) action of no 2.66E−02 3/40 tcga 2 Androgen Receptor wtCFTR and delta508-CFTR traffic/ no 3.26E−02 8/50 tcc 2 Generic schema (norm and CF) wtCFTR and delta508-CFTR traffic/ no 3.70E−02 5/50 mda 2 Generic schema (norm and CF) Apoptosis and survival_Anti-apoptotic no 3.24E−02 7/41 tcc 1 TNFs/NF-kB/Bcl-2 pathway Apoptosis and survival_Beta-2 adrenergic yes 1.32E−03 5/23 mda 1 receptor anti-apoptotic action Apoptosis and survival_Ceramides signaling no 2.66E−02 3/40 tcga 1 pathway Apoptosis and survival_Regulation of no 1.23E−02 4/33 mcc 1 Apoptosis by Mitochondrial Proteins Arachidonic acid production no 4.69E−02 3/50 tcga 1 Atherosclerosis_Role of ZNF202 in no 1.80E−02 5/21 tcc 1 regulation of expression of genes involved in Atherosclerosis Autophagy_Autophagy no 2.96E−02 4/32 mda 1 Bacterial infections in CF airways yes 7.79E−05 14/58  tcc 1 Blood coagulation_GPCRs in platelet no 4.76E−02 6/71 mda 1 aggregation Blood coagulation_GPIb-IX-V-dependent no 3.31E−02 4/75 tcga 1 platelet activation Blood coagulation_GPVI-dependent platelet yes 2.37E−03 11/55  tcc 1 activation C and CxC3 Chemokines no 4.90E−02 2/5  tcc 1 cAMP/Ca(2+)-dependent Insulin secretion no 2.07E−02 5/43 mda 1 Cannabinoid receptor signaling in nicotine no 3.60E−02 4/34 mda 1 addiction Cardiac Hypertrophy_Ca(2+)-dependent yes 3.94E−05 10/57  mda 1 NF-AT signaling in Cardiac Hypertrophy Cardiac Hypertrophy_NF-AT signaling in yes 1.26E−04 10/65  mda 1 Cardiac Hypertrophy Catecholamine metabolism no 2.91E−02 4/72 tcga 1 Catecholamine metabolism/Human version no 3.04E−02 4/73 tcga 1 CC chemokines/receptor faimly CC15- no 4.87E−02 2/22 tcga 1 CCL28 Cell adhesion_Alpha-4 integrins in cell no 4.00E−02 6/34 tcc 1 migration and adhesion Cell adhesion_Endothelial cell contacts by no 3.11E−02 5/24 tcc 1 non-junctional mechanisms Cell adhesion_Gap junctions no 1.23E−02 3/30 tcga 1 Cell adhesion_Integrin-mediated cell no 4.24E−02 3/48 tcga 1 adhesion and migration Cell cycle_Influence of Ras and Rho no 1.05E−02 4/53 tcga 1 proteins on G1/S Transition CFTR folding and maturation (norm and no 1.36E−02 3/14 mda 1 CF) Chemotaxis_CCR4-induced chemotaxis of no 1.22E−02 7/34 tcc 1 immune cells CXC Chemokine-receptor family yes 4.45E−04 7/20 tcc 1 Cytokine production by Th17 cells in CF no 2.52E−02 7/39 tcc 1 Cytokine production by Th17 cells in CF no 9.10E−03 6/49 mda 1 (Mouse model) Cytoskeleton remodeling_Alpha-1A no 3.72E−02 2/19 tcga 1 adrenergic receptor-dependent inhibition of PI3K Cytoskeleton remodeling_CDC42 in cellular yes 8.57E−04 7/22 tcc 1 processes Cytoskeleton remodeling_Cytoskeleton no 2.47E−02  5/102 tcga 1 remodeling Cytoskeleton remodeling_Neurofilaments no 7.37E−03 3/25 tcga 1 Cytoskeleton remodeling_Regulation of no 5.81E−03 3/23 tcga 1 actin cytoskeleton by Rho GTPases Cytoskeleton remodeling_Role of PDGFs in no 1.10E−02 4/24 mda 1 cell migration Cytoskeleton remodeling_Role of PKA in no 2.86E−02 7/40 tcc 1 cytoskeleton reorganisation Cytoskeleton remodeling_Thyroliberin in no 6.89E−03 5/33 mda 1 cytoskeleton remodeling dCTP/dUTP metabolism no 3.31E−02 4/75 tcga 1 Development_A2A receptor signaling no 4.08E−02 7/43 tcc 1 Development_A3 receptor signaling no 3.43E−02 5/49 mda 1 Development_ACM2 and ACM4 activation no 2.07E−02 5/43 mda 1 of ERK Development_Activation of ERK by Kappa- no 4.32E−02 4/36 mda 1 type opioid receptor Development_Alpha-2 adrenergic receptor no 1.78E−02 4/62 tcga 1 activation of ERK Development_Angiotensin activation of Akt no 2.70E−02 5/46 mda 1 Development_Angiotensin signaling via no 1.27E−02 4/25 mda 1 beta-Arrestin Development_Beta-adrenergic receptors no 7.43E−03 6/47 mda 1 regulation of ERK Development_Beta-adrenergic receptors no 4.28E−02 5/52 mda 1 signaling via cAMP Development_Cross-talk between VEGF no 1.14E−02 6/26 tcc 1 and Angiopoietin 1 signaling pathways Development_EDNRB signaling no 3.70E−02 5/50 mda 1 Development_EGFR signaling pathway no 4.63E−02 9/63 tcc 1 Development_EPO-induced Jak-STAT no 4.53E−02 6/35 tcc 1 pathway Development_EPO-induced MAPK no 5.77E−03 9/45 tcc 1 pathway Development_FGF-family signaling no 1.50E−02 9/52 tcc 1 Development_FGFR signaling pathway no 4.87E−02 8/54 tcc 1 Development_GDNF family signaling no 2.07E−02 8/46 tcc 1 Development_Glucocorticoid receptor no 3.11E−02 5/24 tcc 1 signaling Development_GM-CSF signaling no 4.69E−02 3/50 tcga 1 Development_Growth hormone signaling no 1.43E−02 7/35 tcc 1 via STATs and PLC/IP3 Development_Hedgehog and PTH signaling no 2.85E−03 5/36 mcc 1 pathways in bone and cartilage development Development_HGF signaling pathway no 9.09E−03 5/47 mcc 1 Development_Inhibition of angiogenesis by no 2.66E−02 4/31 mda 1 PEDF Development_Melanocyte development and no 9.10E−03 6/49 mda 1 pigmentation Development_Mu-type opioid receptor no 7.59E−03 6/24 tcc 1 signaling via Beta-arrestin Development_Osteopontin signaling in no 6.02E−03 7/30 tcc 1 osteoclasts Development_Oxytocin receptor signaling yes 3.30E−03 6/40 mda 1 Development_PACAP signaling in neural no 1.40E−02 5/39 mda 1 cells Development_PDGF signaling via MAPK no 2.93E−02 5/47 mda 1 cascades Development_Prolactin receptor signaling no 2.13E−02 5/58 mcc 1 Development_Regulation of CDK5 in CNS no 4.07E−02 3/28 mcc 1 Development_Regulation of telomere length no 1.43E−02 7/35 tcc 1 and cellular immortalization Development_Role of HDAC and no 4.91E−02 5/54 mda 1 calcium/calmodulin-dependent kinase (CaMK) in control of skeletal myogenesis Development_S1P1 signaling pathway no 5.36E−03 6/44 mda 1 Development_S1P2 and S1P3 receptors in no 8.23E−03 3/26 tcga 1 cell proliferation and differentiation Development_S1P3 receptor signaling no 4.77E−03 6/43 mda 1 pathway Development_Signaling of Beta-adrenergic no 4.25E−02 5/26 tcc 1 receptors via Beta-arrestins Development_Slit-Robo signaling no 4.53E−03 5/30 mda 1 Development_SSTR2 in regulation of cell no 1.00E−02 5/36 mda 1 proliferation Development_TGF-beta-dependent no 7.43E−03 6/47 mda 1 induction of EMT via MAPK Development_Thrombopoetin signaling via no 2.16E−02 3/22 mcc 1 JAK-STAT pathway Development_Thrombopoietin-regulated no 5.87E−03 4/45 tcga 1 cell processes Development_Thyroliberin signaling no 7.10E−03 7/61 mda 1 Development_WNT signaling pathway. Part no 1.16E−02 5/19 tcc 1 1. Degradation of beta-catenin in the absence WNT signaling Development_WNT5A signaling no 2.70E−02 5/46 mda 1 Glycolysis and gluconeogenesis p.3 no 2.73E−02 3/24 mcc 1 Glycolysis and gluconeogenesis p.3/ no 2.73E−02 3/24 mcc 1 Human version G-protein signaling_G-Protein beta/gamma no 7.84E−03 5/34 mda 1 signaling cascades G-protein signaling_RAC1 in cellular yes 1.85E−04 10/35  tcc 1 process G-protein signaling_Rap2A regulation no 2.34E−02 3/17 mda 1 pathway G-protein signaling_Regulation of cAMP no 2.48E−02 5/45 mda 1 levels by ACM G-protein signaling_RhoB regulation yes 7.60E−04 6/16 tcc 1 pathway GTP metabolism no 1.44E−02 6/54 mda 1 Immune response_CCR3 signaling in yes 1.69E−03 14/77  tcc 1 eosinophils Immune response_IFN gamma signaling no 6.55E−03 10/54  tcc 1 pathway Immune response_Sialic-acid receptors yes 7.78E−06 7/12 tcc 1 (Siglecs) signaling Immune response_Antigen presentation by no 9.84E−03 4/12 tcc 1 MHC class II Immune response_Antiviral actions of yes 3.93E−04 12/52  tcc 1 Interferons Immune response_Bacterial infections in no 3.69E−03 10/50  tcc 1 normal airways Immune response_BCR pathway no 1.89E−02 9/54 tcc 1 Immune response_CCR5 signaling in no 2.00E−02 6/58 mda 1 macrophages and T lymphocytes Immune response_CD137 signaling in no 1.12E−02 3/29 tcga 1 immune cell Immune response_CD16 signaling in NK no 3.37E−02 10/69  tcc 1 cells Immune response_Fc epsilon RI pathway no 7.48E−03 10/55  tcc 1 Immune response_Fc gamma R-mediated no 7.76E−03 9/47 tcc 1 phagocytosis in macrophages Immune response_Function of MEF2 in T no 1.00E−02 6/50 mda 1 lymphocytes Immune response_Histamine H1 receptor no 3.17E−02 5/48 mda 1 signaling in immune response Immune response_Histamine signaling in no 3.70E−02 5/50 mda 1 dendritic cells Immune response_HMGB1/RAGE signaling yes 1.17E−04 13/53  tcc 1 pathway Immune response_HMGB1/TLR signaling yes 1.13E−03 9/36 tcc 1 pathway Immune response_ICOS pathway in T- no 6.71E−03 9/46 tcc 1 helper cell Immune response_IFN alpha/beta signaling yes 4.25E−06 10/24  tcc 1 pathway Immune response_IL-1 signaling pathway no 4.54E−02 7/44 tcc 1 Immune response_IL-10 signaling pathway no 1.46E−02 4/26 mda 1 Immune response_IL-7 signaling in B no 4.99E−03 4/43 tcga 1 lymphocytes Immune response_IL-7 signaling in T no 3.17E−03 4/38 tcga 1 lymphocytes Immune response_Immunological synapse yes 1.31E−03 12/59  tcc 1 formation Immune response_Inhibitory action of no 4.02E−02 3/47 tcga 1 Lipoxins on pro-inflammatory TNF-alpha signaling Immune response_Inhibitory action of no 4.29E−03 10/51  tcc 1 lipoxins on superoxide production induced by IL-8 and Leukotriene B4 in neutrophils Immune response_Innate immune response no 1.64E−02 6/28 tcc 1 to RNA viral infection Immune response_NFAT in immune yes 3.24E−04 12/51  tcc 1 response Immune response_PIP3 signaling in B no 3.56E−03 9/42 tcc 1 lymphocytes Immune response_Role of DAP12 receptors no 4.87E−02 8/54 tcc 1 in NK cells Immune response_Role of HMGB1 in no 3.20E−03 7/27 tcc 1 dendritic cell maturation and migration Immune response_Role of integrins in NK no 2.21E−02 7/38 tcc 1 cells cytotoxicity Immune response_Role of the Membrane no 3.60E−02 4/34 mda 1 attack complex in cell survival Immune response_T cell receptor signaling no 1.50E−02 9/52 tcc 1 pathway Immune response_TCR and CD28 co- no 9.06E−03 8/40 tcc 1 stimulation in activation of NF-kB Immune response_Th17 cell differentiation no 3.88E−03 8/35 tcc 1 Immune response_TLR signaling pathways no 8.50E−03 10/56  tcc 1 Inhibitory action of Lipoxins on Superoxide no 3.16E−03 10/49  tcc 1 production in neutrophils Mechanism of action of CCR4 antagonists no 1.22E−02 7/34 tcc 1 in asthma and atopic dermatitis (Variant 1) Membrane-bound ESR1: interaction with G- no 3.59E−03 7/54 mda 1 proteins signaling Mucin expression in CF via IL-6, IL-17 no 4.00E−02 6/34 tcc 1 signaling pathways Muscle contraction_ACM regulation of no 2.36E−02 9/56 tcc 1 smooth muscle contraction Muscle contraction_GPCRs in the regulation no 1.16E−02 8/83 mda 1 of smooth muscle tone Muscle contraction_Oxytocin signaling in no 6.49E−03 7/60 mda 1 uterus and mammary gland Muscle contraction_Regulation of eNOS no 4.42E−03 7/56 mda 1 activity in cardiomyocytes Muscle contraction_Regulation of eNOS no 9.20E−03 7/64 mda 1 activity in endothelial cells Muscle contraction_Relaxin signaling no 8.23E−03 6/48 mda 1 pathway Neurophysiological process_ACM yes 1.40E−03 7/46 mda 1 regulation of nerve impulse Neurophysiological process_Dopamine D2 no 2.93E−02 5/47 mda 1 receptor signaling in CNS Neurophysiological process_EphB receptors no 1.43E−02 7/35 tcc 1 in dendritic spine morphogenesis and synaptogenesis Neurophysiological process_GABA-A no 1.38E−02 6/27 tcc 1 receptor life cycle Neurophysiological process_Glutamate no 1.82E−02 8/45 tcc 1 regulation of Dopamine D1A receptor signaling Neurophysiological process_Long-term no 9.10E−03 6/49 mda 1 depression in cerebellum Neurophysiological process_Melatonin no 2.07E−02 5/43 mda 1 signaling Neurophysiological process_Mu-type opioid no 2.39E−02 4/30 mda 1 receptor-mediated analgesia Neurophysiological process_NMDA- no 9.39E−03 8/80 mda 1 dependent postsynaptic long-term potentiation in CA1 hippocampal neurons NGF activation of NF-kB no 1.12E−02 3/29 tcga 1 Nicotine signaling in glutamatergic neurons yes 1.18E−03 6/33 mda 1 Normal and pathological TGF-beta- no 1.23E−02 4/33 mcc 1 mediated regulation of cell proliferation O-glycan biosynthesis no 7.04E−03 11/63  tcc 1 O-glycan biosynthesis/Human version no 7.04E−03 11/63  tcc 1 Oxidative stress_Angiotensin II-induced no 1.43E−02 7/35 tcc 1 production of ROS Polyamine metabolism no 2.42E−02 4/68 tcga 1 Possible influence of low doses of Arsenite no 1.01E−02 3/28 tcga 1 on glucose uptake in muscle Protein folding_Membrane trafficking and yes 5.17E−04 5/19 mda 1 signal transduction of G-alpha (i) heterotrimeric G-protein Proteolysis_Putative SUMO-1 pathway no 2.13E−02 4/29 mda 1 Putative pathways for stimulation of fat cell no 3.06E−02 6/32 tcc 1 differentiation by Bisphenol A Regulation of CFTR activity (norm and CF) yes 1.25E−03 8/58 mda 1 Regulation of lipid metabolism_Alpha-1 no 2.65E−02 4/70 tcga 1 adrenergic receptors signaling via arachidonic acid Regulation of lipid metabolism_G-alpha(q) no 3.20E−02 9/59 tcc 1 regulation of lipid metabolism Regulation of lipid metabolism_Regulation no 6.00E−03 6/45 mda 1 of lipid metabolism by niacin and isoprenaline Regulation of lipid metabolism_Stimulation no 2.91E−02 4/72 tcga 1 of Arachidonic acid production by ACM receptors Reproduction_GnRH signaling no 3.54E−03 7/72 mcc 1 Serotonin-melatonin biosynthesis and no 4.93E−02 3/51 tcga 1 metabolism Signal transduction_Calcium signaling yes 1.22E−03 7/45 mda 1 Signal transduction_Erk Interactions: yes 1.39E−03 6/34 mda 1 Inhibition of Erk Signal transduction_IP3 signaling no 9.10E−03 6/49 mda 1 Stem cell marker (Nanog, Sox2, Oct4, no 1.81E−02 3/8  tcc 1 CD133, Nestin) Transcription_ChREBP regulation pathway no 6.76E−03 4/21 mda 1 Transcription_CREB pathway no 2.93E−02 5/47 mda 1 Transcription_NF-kB signaling pathway yes 2.07E−03 9/39 tcc 1 Transcription_Role of Akt in hypoxia no 5.98E−03 4/27 mcc 1 induced HIF1 activation Transcription_Transcription regulation of no 3.04E−02 3/25 mcc 1 aminoacid metabolism Transport_ACM3 in salivary glands no 4.24E−03 6/42 mda 1 Transport_Aldosterone-mediated regulation no 2.39E−02 4/30 mda 1 of ENaC sodium transport Transport_Alpha-2 adrenergic receptor yes 1.59E−03 7/47 mda 1 regulation of ion channels Transport_Macropinocytosis regulation by no 8.46E−03 7/63 mda 1 growth factors Tyrosine metabolism p.1 (dopamine) no 1.98E−02 4/64 tcga 1 Untitled no 2.76E−02 1/1  mcc 1 wtCFTR and deltaF508 traffic/Membrane no 3.60E−02 4/34 mda 1 expression (norm and CF)

TABLE 7 Pearson's correlation for Integrin Drugs Bonferroni NSC Adjusted p- No. Compound Name Pearson Score p-value value 676497 TP4EK 0.766727885 2.28E−12 5.24E−08 676495 NA 0.751476854 1.07E−11 2.46E−07 671526 TOXIN .DELTA.53L 0.736035292 4.61E−11 1.06E−06 688718 NA −0.700760613 6.44E−10 1.48E−05 723742 Diethyl N[4-[(3-phenyl-5,7- −0.706925314 1.14E−09 2.62E−05 diaminoquinoxalin-2-yl)amino]benzoyl]-L-glutamate 723740 Diethyl N-[-[(3-phenyl-5,7- −0.690810438 1.40E−09 3.22E−05 diaminoquinoxalin-2- yl)aminomethyl]benzoyl]-L-gluatamate 645157 4,7-[Bis-N,N′-(3-amino-9-thioacetamido)- −0.682148303 2.70E−09 6.21E−05 acridine]-biphenyl 716261 NA 0.698290184 3.09E−09 7.11E−05 680073 NA −0.674463414 4.72E−09 0.000108569 699428 NA −0.673855388 6.73E−09 0.000154803 35049 NA −0.667543843 7.72E−09 0.000177575 687978 NA −0.693298313 8.72E−09 0.000200577 712623 NA −0.687454524 9.37E−09 0.000215529 623436 TGF.alpha.-PE40 0.721444283 1.06E−08 0.000243821 369318 NA −0.661991143 1.13E−08 0.000259923 704609 NA −0.67995242 1.14E−08 0.000262223 635157 Dichlorobisoxinatotitanium(IV) −0.722426059 1.45E−08 0.000333529 703315 NA −0.670789286 1.54E−08 0.000354231 633207 NA −0.709546693 1.64E−08 0.000377233 616511 NA 0.662658493 1.96E−08 0.000450839 625495 1-Piperidinecarbodithioic acid, antimony −0.650579578 2.44E−08 0.000561249 complex 723001 Diethyl-N[4-(3-thienylquinoxalyn-2- 0.659986786 3.15E−08 0.000724563 yl)oxiphenylacetyl]-L-glutamate 677960 16.beta.-N-methylpiperazino-5-androstene- −0.645051147 3.50E−08 0.00080507 3.beta.,17.beta.-diol-diacetate 716729 NA −0.655806396 4.11E−08 0.000945382 677395 2-Azido-10-[(4- −0.641851353 4.29E−08 0.000986786 dimethylamino)butyl]phenothiazine, oxalate salt 625502 4-Morpholinecarbodithioic acid, antimony −0.641295412 4.45E−08 0.001023589 complex 2186 Thymophthalein, 1(3H)-Isobenzofuranone, −0.639442901 5.00E−08 0.0011501 3,3-bis[4-hydroxy-2-methyl-5-(1- methylethyl)phenyl]- 351075 1H-Azepine-1-carbothioic acid, hexahydro-, −0.648145415 5.02E−08 0.0011547 [1-(2-pyridinyl)ethylidene]hydrazide, N- oxide 17474 SKF 5019, Eskazine, Calmazine −0.639354768 5.03E−08 0.001157001 13984 NA −0.639206645 5.07E−08 0.001166201 627050 Dispiro[cyclopropane-1,2′(3′H)-naphthalene- −0.639055416 5.12E−08 0.001177702 3′,2″-imidazolidine], 1″,3″-dimethyl- 686324 Indolizine, 1-methyl-3-[4-[2- −0.636942362 5.85E−08 0.001345617 (dimethylamino)ethoxy]phenyl]-2-phenyl- 700422 NA −0.640908346 5.98E−08 0.00137552 11225 Klot, Blutene, Toluidine Blue O −0.636039696 6.19E−08 0.001423824 676879 Phenothiazine, 2-azido-10-[4-(4-methyl-1- −0.639940972 6.36E−08 0.001462927 piperazinyl)butyl]-, difumarate 701666 Benzenamine, N-[4-(4-chlorophenyl)-3-(2- −0.648677587 6.43E−08 0.001479029 propenyl)-2(3H)-thiazolylidene]-2-methoxy-, hydrobromide, (2Z)- 657562 2-[(Z)-bromoiodomethylidene] −0.634417368 6.84E−08 0.001573337 cyclohexanone 708089 NA −0.63408625 6.99E−08 0.00160784 34924 NA −0.631194088 8.35E−08 0.001920667 742850 NA −0.630058793 8.95E−08 0.002058679 715472 NA −0.633788471 9.28E−08 0.002134586 716535 NA −0.628790703 9.67E−08 0.002224293 641056 NA −0.675691328 1.00E−07 0.0023002 679749 NA −0.641398269 1.00E−07 0.0023002 676498 TP4EK-K6 0.632034958 1.03E−07 0.002369206 682932 NA 0.640707558 1.05E−07 0.00241521 684411 NA −0.645241923 1.05E−07 0.00241521 685016 NA −0.635434747 1.10E−07 0.00253022 641220 NA −0.639578183 1.12E−07 0.002576224 687976 NA −0.648879965 1.12E−07 0.002576224 675006 NA −0.639227622 1.14E−07 0.002622228 631522 NA −0.634530774 1.16E−07 0.002668232 658215 1H,5H-Benzo[ij]quinolizine-5-one, 7-azido- −0.629718727 1.19E−07 0.002737238 2,3-dihydro-6-nitro- 660634 2-Chloro-3-(2-chloroethoxy)-naphthazarin −0.643044568 1.20E−07 0.00276024 741338 12-Benzyl-5,12-dihydro- 0.633441773 1.23E−07 0.002829246 indeno[2′,1′:4,5]pyrrolo[3,2-c]chinolin-6,7- dione 692583 NA −0.641429714 1.32E−07 0.003036264 686368 Quinazolin-4(3H)-one, 3-ethyl-2-[[[5- 0.627785195 1.33E−07 0.003059266 (phenylamino)-1,3,4-thiadiazol-2- yl]methyl]thio]- 715690 NA 0.630136941 1.50E−07 0.0034503 116532 NA −0.622772645 1.79E−07 0.004117358 691220 NA 0.630535419 1.91E−07 0.004393382 732517 Dasatinib 0.616761441 1.98E−07 0.004554396 711830 NA −0.639031012 1.99E−07 0.004577398 697882 NA −0.625076405 2.02E−07 0.004646404 665689 NA −0.61600903 2.07E−07 0.004761414 709922 Landomycin E −0.615886676 2.08E−07 0.004784416 695332 NA 0.657261403 2.16E−07 0.004968432 252188 2,5-Cyclohexadiene-1,4-dione, 2-chloro-5,6- −0.619277844 2.19E−07 0.005037438 dimethoxy-3-(octylthio)- 716294 NA −0.636503239 2.30E−07 0.00529046 682300 NA −0.617465383 2.43E−07 0.005589486 635322 NA −0.664949195 2.54E−07 0.005842508 335791 3-Azabicyclo[3.2.2]nonane-3-carbothioic −0.614728899 2.84E−07 0.006532568 acid, [1-(2-pyridinyl)butylidene]hydrazide 644583 NA −0.662436695 2.92E−07 0.006716584 688816 NA 0.613706891 3.01E−07 0.006923602 639386 NA −0.67850119 3.02E−07 0.006946604 715486 NA −0.61359876 3.03E−07 0.006969606 702397 NA 0.612845334 3.16E−07 0.007268632 635308 NA −0.671652795 3.22E−07 0.007406644 304379 NA −0.625773257 3.24E−07 0.007452648 644933 NA −0.650080298 3.24E−07 0.007452648 354671 1-Piperazinecarbothioic acid, 4-(2- −0.606816872 3.49E−07 0.008027698 pyridinyl)-, [1-(2- thiazolyl)ethylidene]hydrazide 710404 NA −0.606388072 3.58E−07 0.008234716 660632 2-Chloro-3-[2-(2-butoxyethoxy)ethoxy]- −0.619351079 3.60E−07 0.00828072 naphthazarin 303612 LM 209, Virginan, Mequitazine −0.605774639 3.70E−07 0.00851074 246981 NA −0.608689581 3.99E−07 0.009177798 735179 (1,1-dioxido-3-oxo-1,2-benzisothiazol- −0.604344993 4.01E−07 0.009223802 2(3H)-yl)methyl diethyldithiocarbamate 671409 NA 0.607992724 4.15E−07 0.00954583 666075 1,1-diiodo-2,2-dimethoxy-2-phenylethane −0.607935343 4.16E−07 0.009568832 625501 Antimony, chlorobis(1- −0.603385633 4.23E−07 0.009729846 piperidinecarbodithioato-S,S′)- 684480 7H-Pyrido[3,2-d][1]benzazepin-6-one, 2-(3- 0.603028503 4.32E−07 0.009936864 chlorophenyl)-5,6-dihydro-4-phenyl-

TABLE 8 Pearson's correlation for WNT2 drugs Bonferroni NSC No. Compound Name Pearson Score p-value Adjusted p-value 724325 NA −0.710613594 5.93E−10 1.36E−05 150412 NA 0.6828783 3.53E−09 8.12E−05 680313 NA −0.668529078 7.20E−09 0.000165614 711070 NA −0.67727365 7.24E−09 0.000166534 674493 Hydrazinecarboxamide, N-(1-naphthyl)-2-[(4- −0.661389005 1.18E−08 0.000271424 nitrophenyl)methylene]- 678057 Pyridine-3-carbonitrile, 6-(4-chlorophenyl)-1- −0.660202214 1.28E−08 0.000294426 (.beta.-D-glucopyranosyl)-1,2-dihydro-2- thioxo-, 2′,3′,4′,6′-tetraacetate 630375 2H-1-Benzopyran-2-one, 4-(2-benzofuranyl)- −0.658161133 2.64E−08 0.000607253 7-methoxy- 702397 NA −0.651626077 3.03E−08 0.000696961 635157 Dichlorobisoxinatotitanium(IV) 0.709975874 3.29E−08 0.000756766 672768 NA −0.65232352 3.85E−08 0.000885577 135371 NA 0.647588118 3.93E−08 0.000903979 354670 3-Azabicyclo[3.2.2]nonane-3-carbothioic acid, 0.642865361 4.02E−08 0.00092468 [1-(2-thiazolyl)ethylidene]hydrazide 682817 7,10:11,14-Dietheno-28H-23,27-nitrilo-22H- −0.642149215 4.21E−08 0.000968384 dibenzo[b,p] [1,18,5,14]dioxadiazacyclopentacosine 645392 2-Propen-1-one, 1-(4-chlorophenyl)-3-[4-[2- −0.642046828 4.24E−08 0.000975285 oxo-2-(4-phenyl-1- piperazinyl)ethoxy]phenyl]-, (E)- 670782 NA 0.640394693 4.71E−08 0.001083394 625542 Methanone, phenyl-2-pyridyl-, 2- 0.637130403 5.78E−08 0.001329516 pyridylhydrazone, nickel acetate complex 668836 NA −0.662104347 6.70E−08 0.001541134 650792 1,4,7,10-Tetrathia-13-azacyclopentadecane, −0.632373275 7.77E−08 0.001787255 13-[(4-methylphenyl)sulfonyl]- 351078 Hydrazinecarbothioamide, N,N-dimethyl-2-[1- 0.628686077 9.73E−08 0.002238095 (2-pyridinyl)-ethylidene]-, N-oxide 742036 NA −0.656281605 1.28E−07 0.002944256 657562 2-[(Z)-bromoiodomethylidene] cyclohexanone 0.622000673 1.45E−07 0.00333529 647133 NA 0.66907426 1.48E−07 0.003404296 677640 NA −0.621411198 1.50E−07 0.0034503 682504 NA −0.620249301 1.61E−07 0.003703322 685848 4(3H)-Quinazolinone, 3-[[(2- −0.623088892 1.76E−07 0.004048352 nitrophenyl)methylene]amino]-2-phenyl- 716535 NA 0.618478624 1.79E−07 0.004117358 745449 NA 0.617892232 1.85E−07 0.00425537 625543 ANTINEOPLASTIC-625543 0.616754535 1.98E−07 0.004554396 682932 NA −0.629475374 2.03E−07 0.004669406 622613 3H-Naphtho[1,8-bc]furan-2-carboxylic acid, −0.617922148 2.37E−07 0.005451474 4,5-dihydro-6-nitro-, ethyl ester 166588 METHYLUNDECYLPIPERIDINE, TRANS 0.612415173 2.54E−07 0.005842508 321206 NA 0.609213968 3.05E−07 0.00701561 736442 7-fluoro-2-(thien-2-ilcarbonyl)-3- 0.60831884 3.21E−07 0.007383642 trifluoromethylquioxaline 1,4-dioxide 715648 NA −0.607728018 3.32E−07 0.007636664 683922 NA 0.60713614 3.43E−07 0.007889686 637921 1H-Pyrazole-1-propanamide, 3,5-diphenyl-N- −0.606346286 3.59E−07 0.008257718 (4-methoxyphenyl)-4-[(4-methylphenyl)azo]- .beta.-oxo- 176632 Stannane, trimethyl[(4- 0.675314344 3.60E−07 0.00828072 morpholinylthioxomethyl)thio]- 691422 acetonitrile, dimethoxyphenyl, pyrimidin −0.609371891 3.84E−07 0.008832768 691415 NA −0.604707722 3.93E−07 0.009039786 711222 NA −0.604718705 3.93E−07 0.009039786 338304 Iron, dichloro[hexahydro-1H-azepine-1- 0.603615641 4.18E−07 0.009614836 carbothioic acid [1-(2- pyridinyl)ethylidene]hydraziato] 667722 NA −0.634935881 4.29E−07 0.009867858

TABLE 9 Pearson's correlation for TGF-WNT drugs Bonferroni NSC No. Compound Name Pearson Score p-value Adjusted p-value 682932 NA 0.778356256 1.66E−12 3.82E−08 661232 2-(4-hydroxybenzylidene)-5-((phenyl- −0.769299612 1.73E−12 3.98E−08 amino)methyl)cyclopentanone 635131 NA −0.806525613 4.54E−12 1.04E−07 645157 4,7-[Bis-N,N′-(3-amino-9-thioacetamido)-acridine]- −0.753473538 5.74E−12 1.32E−07 biphenyl 354671 1-Piperazinecarbothioic acid, 4-(2-pyridinyl)-, [1-(2- −0.752586626 6.27E−12 1.44E−07 thiazolyl)ethylidene]hydrazide 736442 7-fluoro-2-(thien-2-ilcarbonyl)-3- −0.746277988 1.17E−11 2.69E−07 trifluoromethylquioxaline 1,4-dioxide 351075 1H-Azepine-1-carbothioic acid, hexahydro-, [1-(2- −0.752883461 1.43E−11 3.29E−07 pyridinyl)ethylidene]hydrazide, N-oxide 670782 NA −0.741846529 1.79E−11 4.12E−07 351078 Hydrazinecarbothioamide, N,N-dimethyl-2-[1-(2- −0.740214447 2.09E−11 4.81E−07 pyridinyl)-ethylidene]-, N-oxide 717769 NA −0.737729565 2.64E−11 6.07E−07 354670 3-Azabicyclo[3.2.2]nonane-3-carbothioic acid, [1-(2- −0.736446198 2.98E−11 6.85E−07 thiazolyl)ethylidene]hydrazide 735181 (1,1-dioxido-3-oxo-1,2-benzisothiazol-2(3H)- −0.739547945 3.34E−11 7.68E−07 yl)methyl 4-methylpiperazine-1-carbodithioate 680072 Ochraceolide A −0.733329843 3.97E−11 9.13E−07 635157 Dichlorobisoxinatotitanium(IV) −0.794330317 4.45E−11 1.02E−06 166588 METHYLUNDECYLPIPERIDINE, TRANS −0.729674697 5.54E−11 1.27E−06 689279 NA −0.74663529 5.97E−11 1.37E−06 618059 1-Penten-3-one, 5-(4-morpholinyl)-1-phenyl-, −0.737077947 6.26E−11 1.44E−06 hydrochloride 135371 NA −0.732185189 6.53E−11 1.50E−06 691422 acetonitrile, dimethoxyphenyl, pyrimidin 0.730371627 7.68E−11 1.77E−06 639617 NA −0.722380828 1.06E−10 2.44E−06 625542 Methanone, phenyl-2-pyridyl-, 2-pyridylhydrazone, −0.722307568 1.07E−10 2.46E−06 nickel acetate complex 682866 Ethanone, 1-[7-(4-chlorophenyl)-5,6-dihydro-9- −0.724082351 1.33E−10 3.06E−06 methyl-7H-benzo[h]thiazolo[2,3-b]quinazolin-10-yl]- 716535 NA −0.719557758 1.35E−10 3.11E−06 630375 2H-1-Benzopyran-2-one, 4-(2-benzofuranyl)-7- 0.725397007 1.74E−10 4.00E−06 methoxy- 745449 NA −0.716570478 1.75E−10 4.03E−06 35949 NA −0.716500964 1.76E−10 4.05E−06 657562 2-[(Z)-bromoiodomethylidene] cyclohexanone −0.716273257 1.79E−10 4.12E−06 672768 NA 0.723956796 1.97E−10 4.53E−06 685485 NA −0.725536895 2.53E−10 5.82E−06 682990 Withafastuosin D diacetate −0.716487305 2.55E−10 5.87E−06 688718 NA −0.71101908 2.79E−10 6.42E−06 640927 NA −0.769114997 4.27E−10 9.82E−06 124784 NA −0.746146175 5.01E−10 1.15E−05 335791 3-Azabicyclo[3.2.2]nonane-3-carbothioic acid, [1-(2- −0.706043967 5.99E−10 1.38E−05 pyridinyl)butylidene]hydrazide 620674 NA 0.764730078 6.15E−10 1.41E−05 319447 NA −0.705228379 6.39E−10 1.47E−05 646162 NA −0.742503567 6.73E−10 1.55E−05 711474 NA −0.726537639 7.36E−10 1.69E−05 622696 Thioperoxydicarbonic diamide, tetramethyl- −0.703386618 7.40E−10 1.70E−05 626881 NA −0.734501928 8.53E−10 1.96E−05 13984 NA −0.696932095 8.72E−10 2.01E−05 736443 7-fluoro-2-(2-furoyl)-3-trifluoromethylquioxaline 1,4- −0.696803932 8.81E−10 2.03E−05 dioxide 645392 2-Propen-1-one, 1-(4-chlorophenyl)-3-[4-[2-oxo-2-(4- 0.695091956 1.01E−09 2.32E−05 phenyl-1-piperazinyl)ethoxy]phenyl]-, (E)- 695320 NA 0.722078326 1.05E−09 2.42E−05 622579 Carbamimidothioic acid, N,N-dimethyl-N′- −0.693477682 1.14E−09 2.62E−05 [(phenylimino) (methylthio)methyl]-, phenylmethyl ester, hydroiodide 672464 NA −0.692483163 1.23E−09 2.83E−05 630128 Trichlorotris-3-(t-butyl)pyrazoleruthenium(III) −0.699003864 1.47E−09 3.38E−05 716261 NA 0.708143378 1.48E−09 3.40E−05 639518 Cyclopentanone, 2-[[4-(benzoyloxy)-3- −0.689508702 1.55E−09 3.57E−05 methoxyphenyl] methylene]-5- [(dimethylamino)methyl]-, hydrochloride 616362 2-Methoxycarbonyl-3,4-dichloro-5-nitrofuran −0.689270154 1.58E−09 3.63E−05 707098 NA 0.711791456 1.60E−09 3.68E−05 73109 NA −0.693321966 1.62E−09 3.73E−05 724325 NA 0.697302962 1.68E−09 3.86E−05 656909 NA 0.710973829 1.70E−09 3.91E−05 637921 1H-Pyrazole-1-propanamide, 3,5-diphenyl-N-(4- 0.686537316 1.94E−09 4.46E−05 methoxyphenyl)-4-[(4-methylphenyl)azo]-.beta.-oxo- 658873 NA −0.708992013 1.98E−09 4.55E−05 301457 Cycloalkannin −0.69032212 2.03E−09 4.67E−05 711070 NA 0.69448207 2.08E−09 4.78E−05 702397 NA 0.689732966 2.12E−09 4.88E−05 9291 Naphthol blue, Benzo[a]phenoxazinium, 9- −0.727580409 2.16E−09 4.97E−05 (dimethylamino)-, chloride 711222 NA 0.684305482 2.30E−09 5.29E−05 716431 NA −0.716425863 2.34E−09 5.38E−05 629738 1-Naphthalenecarboxamide,N,N′-1,8-(octanediyl)bis- 0.697276026 2.37E−09 5.45E−05 645153 9(10H)-Acridinethione, bis[3-[1,1′-biphenyl-2,2′-diyl] −0.683305498 2.47E−09 5.68E−05 (2-aminoacetyl)amino- 715335 NA −0.687461266 2.51E−09 5.77E−05 707828 NA −0.682752254 2.58E−09 5.93E−05 674493 Hydrazinecarboxamide, N-(1-naphthyl)-2-[(4- 0.682213563 2.68E−09 6.16E−05 nitrophenyl)methylene]- 645979 NA −0.690372774 2.82E−09 6.49E−05 88871 NA −0.679569766 3.26E−09 7.50E−05 641396 1H-Benzo[a]carbazole-1,4(11H)-dione, 8-methoxy-11- −0.688269536 3.29E−09 7.57E−05 methyl- 635418 NA −0.721088004 3.50E−09 8.05E−05 316458 Neplanocin A −0.677770643 3.72E−09 8.56E−05 646161 Propanethioamide, N-hydroxy-N-methyl- −0.677446841 3.81E−09 8.76E−05 678057 Pyridine-3-carbonitrile, 6-(4-chlorophenyl)-1-(.beta.- 0.677218475 3.87E−09 8.90E−05 D-glucopyranosyl)-1,2-dihydro-2-thioxo-, 2′,3′,4′,6′- tetraacetate 661442 NA −0.676640304 4.04E−09 9.29E−05 675208 NA −0.719082529 4.05E−09 9.32E−05 612955 1,5-Dihydroxy-1,5-di(pyridin-3-yl)pentan-3-one −0.67650484 4.08E−09 9.38E−05 35446 PROPIOPHENONE, 3-PHENYL-3-PIPERIDINO- −0.676193635 4.17E−09 9.59E−05 668267 2H-1-Benzopyran-2-one, 3-chloro-7-[(tetrahydro-4- −0.680572446 4.17E−09 9.59E−05 methylene-5-oxo-2-phenyl-2-furanyl)methoxy]-4- methyl- 625543 ANTINEOPLASTIC-625543 −0.676095483 4.20E−09 9.66E−05 662383 2-Bromo-5,8-dihydroxy-3-methyl-1,4-naphthoquinone −0.675908564 4.26E−09 9.80E−05 669598 NA −0.679808474 4.40E−09 0.000101209 671883 NA −0.675010335 4.54E−09 0.000104429 658366 NA −0.679140058 4.62E−09 0.000106269 668258 NA −0.678993295 4.67E−09 0.000107419 621888 Cyclopentanone, 2-[(dimethylamino)methyl]-, −0.678548761 4.82E−09 0.00011087 hydrochloride 657021 NA −0.711165794 4.97E−09 0.00011432 697862 NA −0.672735925 5.35E−09 0.000123061 600060 Hydrazinecarbodithioic acid, [(6-methyl-2-pyridinyl) −0.671941342 5.66E−09 0.000130191 ethylidene]-, methyl ester 695323 NA −0.704312399 5.67E−09 0.000130421 647133 NA −0.718634004 6.08E−09 0.000139852 645167 NA −0.713321612 6.13E−09 0.000141002 687976 NA −0.693252109 6.25E−09 0.000143763 670969 NA −0.674599101 6.39E−09 0.000146983 631888 Chlorobisoximatobismuth(III)-dihydrochloride −0.71218276 6.64E−09 0.000152733 658514 GAB-GELDANAMYCIN −0.669614632 6.67E−09 0.000153423 645151 3-Acridineamine, 9-[[(4-nitrophenyl)methyl]thio]- −0.669574019 6.69E−09 0.000153883 717768 NA −0.669576976 6.69E−09 0.000153883 716522 NA −0.669562222 6.70E−09 0.000154113 630599 NA −0.717204481 6.73E−09 0.000154803 617145 (2,2-Dimethyl)-1,3-propandiyl-bis(2,3- −0.711673108 6.89E−09 0.000158484 dichloro)maleimide 639520 Cyclohexanone, 2-[(2-methoxyphenyl)methylene]-5- −0.668782424 7.08E−09 0.000162854 [(4-morpholinyl)methyl]-, hydrochloride 630684 8-Quinolinecarboxaldehyde, 2-(2,4-dinitrophenyl)-2- 0.682078965 7.11E−09 0.000163544 methyl-hydrazone 34924 NA −0.668596594 7.17E−09 0.000164924 742857 NA −0.668150449 7.40E−09 0.000170215 690983 NA −0.685979248 7.48E−09 0.000172055 681105 Acetic acid, [1,4,7,10-tetraazacyclododecane-1,7- −0.671920346 7.72E−09 0.000177575 diyl]bis 680625 NA 0.704598201 7.91E−09 0.000181946 632899 NA 0.714240069 8.29E−09 0.000190687 660977 2-bromo-8-hydroxy-6-methyl-1,4-naphthoquinone −0.670485996 8.53E−09 0.000196207 658886 NA −0.665742922 8.75E−09 0.000201268 338304 Iron, dichloro[hexahydro-1H-azepine-1-carbothioic −0.665206987 9.08E−09 0.000208858 acid [1-(2-pyridinyl)ethylidene]hydraziato] 675989 1,3-Dithiolo[3,4-d]pyrimidine-2-thione, 5,7-dichloro- −0.664774761 9.36E−09 0.000215299 74663 NA −0.707096039 9.48E−09 0.000218059 625539 Methanone, phenyl-2-pyridinyl-, 2- −0.71226679 9.50E−09 0.000218519 pyridinylhydrazone,trichloroiron complex 661233 NA −0.668824679 9.57E−09 0.000220129 661238 NA −0.668798038 9.59E−09 0.000220589 639539 NA −0.717160971 9.78E−09 0.00022496 697663 NA 0.681115155 1.05E−08 0.000241521 680313 NA 0.663003348 1.06E−08 0.000243821 309883 NA −0.662152673 1.12E−08 0.000257622 658165 NA −0.694264745 1.14E−08 0.000262223 127763 Propanamide, 2,3-dichloro-N-(9,10-dihydro-9,10- −0.660875151 1.22E−08 0.000280624 dioxo-1-anthracenyl)- 636344 NA −0.708187447 1.26E−08 0.000289825 711611 NA −0.668749482 1.31E−08 0.000301326 68093 NA −0.701980767 1.35E−08 0.000310527 677938 NA −0.65936957 1.36E−08 0.000312827 670961 NA −0.663580425 1.37E−08 0.000315127 671888 NA −0.659264612 1.37E−08 0.000315127 632950 NA −0.70122392 1.42E−08 0.000326628 376266 1-Piperazinethiocarboxylic acid, 4-(2-propynyl)-2-[1- −0.66296559 1.43E−08 0.000328929 (2-pyridinyl)ethylidene]hydrazide 722185 6-(2,4-Difluorophenylmethylideneamino)-3-(4- 0.671604346 1.46E−08 0.000335829 fluorophenyl)thiazolo[4,5-d]pyrimidin-6(7H)-one- 2(3H)-thione 641160 NA −0.711225345 1.47E−08 0.000338129 155595 NA −0.700586007 1.48E−08 0.00034043 305978 Herbimycin Herbimycin A −0.722078474 1.48E−08 0.00034043 716984 NA −0.657771963 1.51E−08 0.00034733 640391 Cyclopentanone, 2,5-bis[(dimethylamino)methyl]-, cis-, −0.661561238 1.57E−08 0.000361131 dihydrochloride 635448 Copper, bromo[2-[1-(2-pyridinyl)ethylidene][N,N- −0.66505518 1.67E−08 0.000384133 dimethyl-hydrazinecarbothioamidato-N,N,S]- 684411 NA −0.67402613 1.69E−08 0.000388734 695801 2,11-Diaza-5,8-dioxadodecane,1,12-bis(6-methoxy-2- −0.655761764 1.73E−08 0.000397935 naphthalenyl)-, monohydrochloride 673611 NA −0.664518126 1.74E−08 0.000400235 182855 Eriolangin −0.655342699 1.78E−08 0.000409436 624508 NA −0.708143919 1.80E−08 0.000414036 650935 3,8-Dimethyl-1,2-naphthoquinone −0.696949729 1.89E−08 0.000434738 645640 NA −0.702044157 1.90E−08 0.000437038 684985 NA 0.667370203 1.94E−08 0.000446239 715230 NA −0.658384108 1.94E−08 0.000446239 638287 NA −0.696132137 1.99E−08 0.00045774 658215 1H,5H-Benzo[ij]quinolizine-5-one, 7-azido-2,3- −0.657957791 2.00E−08 0.00046004 dihydro-6-nitro- 658526 NA −0.657959487 2.00E−08 0.00046004 639519 NA −0.695800053 2.03E−08 0.000466941 711759 NA −0.666608765 2.04E−08 0.000469241 650748 NA −0.657335446 2.08E−08 0.000478442 369318 NA −0.652912664 2.09E−08 0.000480742 684983 NA 0.665871174 2.14E−08 0.000492243 668262 NA −0.660872508 2.21E−08 0.000508344 645145 Benzeneamine, 4-[(9-acridinyl)thio]- −0.651607005 2.28E−08 0.000524446 716172 NA −0.651477457 2.30E−08 0.000529046 641056 NA −0.698999248 2.32E−08 0.000533646 670328 NA −0.660012895 2.34E−08 0.000538247 234214 2,5-Cyclohexadiene-1,4-dione, 2,3-dimethoxy-5-(2- −0.651087393 2.36E−08 0.000542847 naphthalenylthio)- 637396 NA −0.714931746 2.38E−08 0.000547448 621179 Spiro[3H-indole-3,2′-oxirane]-2-one, 3′-(4- −0.659301397 2.45E−08 0.000563549 chlorophenylcarbonyl)-1,2-dihydro 697932 NA −0.650458629 2.46E−08 0.000565849 654893 NA −0.668313908 2.47E−08 0.000568149 670787 NA −0.663498263 2.50E−08 0.00057505 38186 Mercury, (p-dioxane-2,5- −0.687521186 2.51E−08 0.00057735 diyldimethylene)bis[(octanoyloxy)- 702131 NA 0.658900577 2.52E−08 0.00057965 666667 NA −0.653058665 2.76E−08 0.000634855 660634 2-Chloro-3-(2-chloroethoxy)-naphthazarin −0.666513015 2.78E−08 0.000639456 710404 NA −0.648394613 2.81E−08 0.000646356 96914 Perfluorobenzophenone, Benzophenone, decafluoro −0.648244928 2.84E−08 0.000653257 646159 NA −0.660736906 3.00E−08 0.00069006 683922 NA −0.647429956 3.00E−08 0.00069006 625350 Benzenepropanoic acid, .beta.(benzoylamino)-.alpha.- 0.647134169 3.06E−08 0.000703861 hydroxy-, (9,10-dihydro-9,10-dioxo-2- anthracenyl)methyl ester (R*,R*) 630686 NA −0.705364933 3.09E−08 0.000710762 671399 4-Imidazolidinethione, 2-imino-1,3-diphenyl-5- −0.651168329 3.12E−08 0.000717662 (phenylimino)- 717903 NA −0.64653219 3.18E−08 0.000731464 703770 C35H43N5O −0.659692666 3.21E−08 0.000738364 689278 NA −0.664139263 3.24E−08 0.000745265 687311 Acridine, 9-[5-(ethylthio)-1,3,4-thiadiazol-2-yl]- −0.646190113 3.25E−08 0.000747565 626875 NA −0.683431618 3.27E−08 0.000752165 695332 NA 0.688535748 3.27E−08 0.000752165 637397 NA −0.688485111 3.28E−08 0.000754466 710268 NA −0.650296004 3.30E−08 0.000759066 335789 3-Azabicyclo[3.2.1]nonane-3-carbothioic acid, [1-(6- −0.650131035 3.33E−08 0.000765967 methyl-2-pyridinyl)ethylidene]hydrazide 699097 NA −0.654577866 3.33E−08 0.000765967 682817 7,10:11,14-Dietheno-28H-23,27-nitrilo-22H- 0.645438569 3.41E−08 0.000784368 dibenzo[b,p] [l,18,5,14]dioxadiazacyclopentacosine (1S,4R,5R,8R,12R,13S)-1,5-dimethyl-9-methylene- 724784 11,14,15,16- −0.64968865 3.43E−08 0.000788969 tetraoxatetracyclo[10.3.1.04,13.08,13]hexadec-10- yl]oxy}-3-hexenyl)oxy]-1,5,-dimethyl-9-methylene- 11,14,15,16- tetraoxatetracyclo[10.3.1.04,13.08,13]hexadecane 208733 Ramentaceone, 7-Methyl juglon −0.645205303 3.46E−08 0.000795869 145611 Rifamycin, 3-[(4-methyl-1-piperazinyl)methyl]- −0.644493898 3.62E−08 0.000832672 638279 NA −0.644241541 3.68E−08 0.000846474 616511 NA 0.652709332 3.76E−08 0.000864875 285166 Oxin, Tumex, 8-Quinolinol −0.648187201 3.78E−08 0.000869476 692587 ethyl-8-(4-chlorophenyl)-4-methyl-2-oxo-6-(thiophen- −0.652474948 3.81E−08 0.000876376 2-yl)-4a,7-dihydro-2H-chromene-3-carboxylate 688816 NA 0.647712652 3.89E−08 0.000894778 648148 NA −0.643302083 3.91E−08 0.000899378 353896 1-Piperazinecarbothioic acid, 4-(2-pyridinyl)-, 2-[1-(1- −0.647336089 3.99E−08 0.00091778 isoquinolinyl)ethyl]hydrazide 711592 NA −0.647288928 4.00E−08 0.00092008 648147 NA −0.642618951 4.09E−08 0.000940782 643134 NA −0.684866713 4.13E−08 0.000949983 710440 NA −0.665061886 4.13E−08 0.000949983 645147 NA −0.70052814 4.21E−08 0.000968384 305821 NA −0.655365182 4.23E−08 0.000972985 663290 2-chloro-3-N-(2′-(R)-hydroxymethylpyrrolidino)- −0.641422442 4.41E−08 0.001014388 naphthazarine 321206 NA −0.641268468 4.45E−08 0.001023589 658872 NA −0.659045691 4.49E−08 0.00103279 710868 NA −0.640735602 4.61E−08 0.001060392 667706 NA −0.653714341 4.70E−08 0.001081094 668836 NA 0.667544405 4.78E−08 0.001099496 624158 Benzenesulfonothioic acid, 4-methyl-,2-butene-1,4- −0.648882092 4.79E−08 0.001101796 diyl ester, (Z)- 382000 2-Propen-1-one, 2-[(dimethylamino)methyl]-1-(2,4- −0.639745758 4.90E−08 0.001127098 dimethyl phenyl)-, hydrochloride 658441 2-Amino-5,8-dihydroxy-1,4-naphthoquinone −0.643721217 5.02E−08 0.0011547 670813 NA −0.638863346 5.18E−08 0.001191504 658143 2-(1-(4-(2-(2- −0.643177834 5.19E−08 0.001193804 Hydroxyethoxy)ethyl)piperazino))naphthazarin 629874 Benzenamine, 4-ethoxy-N-[(4-quinolinyl)methylene]- −0.643106263 5.22E−08 0.001200704 639981 NA −0.643062432 5.23E−08 0.001203005 715648 NA 0.638615543 5.27E−08 0.001212205 696864 NA −0.638534059 5.29E−08 0.001216806 269149 NOGARENE, U-52048 −0.642077218 5.56E−08 0.001278911 690137 NA −0.690632487 5.57E−08 0.001281211 741338 12-Benzyl-5,12-dihydro-indeno[2′,1′:4,5]pyrrolo[3,2- 0.646486028 5.57E−08 0.001281211 c]chinolin-6,7-dione 710780 NA −0.66496948 5.61E−08 0.001290412 645976 Carbamic acid, (7,9-dichloro-2,8-dioxo-1- −0.646343591 5.62E−08 0.001292712 oxaspiro[4.5]deca-6,9-dien-3-yl)-, 1,1-dimethylethyl ester 663291 2-chloro-3-N-(2′-(S)-hydroxymethylpyrrolidino)- −0.637344623 5.70E−08 0.001311114 naphthazarine 720564 NA 0.669571194 5.71E−08 0.001313414 228155 NA −0.637082487 5.80E−08 0.001334116 661734 NA −0.637014058 5.82E−08 0.001338716 118343 RADICININ, Stemphylone −0.694966578 5.96E−08 0.001370919 626110 NA −0.689489477 5.97E−08 0.001373219 664717 NA 0.649840156 5.98E−08 0.00137552 744999 NA −0.640362663 6.19E−08 0.001423824 683258 NA −0.640201281 6.25E−08 0.001437625 672121 2-Hydroxyethylthio-3-methylnaphthoquinone −0.640149159 6.27E−08 0.001442225 684991 NA 0.673006751 6.29E−08 0.001446826 639517 Cyclopentanone, 2-[(4-chlorophenyl)methylene]-5-[(4- −0.635488873 6.40E−08 0.001472128 morpholinyl)methyl]-, hydrochloride 660637 NA −0.653282184 6.43E−08 0.001479029 689871 NA −0.657774765 6.51E−08 0.00149743 34821 2-Propen-1-one, 2-[(dimethylamino)methyl]-1-(2-nitro −0.635020841 6.59E−08 0.001515832 phenyl)-, hydrochloride 615798 NA −0.68239814 6.66E−08 0.001531933 639542 NA −0.677194346 6.66E−08 0.001531933 639499 NA −0.682372669 6.67E−08 0.001534233 176632 Stannane, trimethyl[(4-morpholinylthioxomethyl)thio]- −0.703962025 6.86E−08 0.001577937 709970 NA −0.638604849 6.91E−08 0.001589438 723740 Diethyl N-[-[(3-phenyl-5,7-diaminoquinoxalin-2- −0.633951771 7.04E−08 0.001619341 yl)aminomethyl]benzoyl]-L-gluatamate 691220 NA 0.647134803 7.07E−08 0.001626241 335794 -Piperazinecarbothioic acid, 4-(2-pyridinyl)-, [1-(2- −0.638169284 7.09E−08 0.001630842 pyridinyl)butylidene]hydrazide 687526 NA −0.633790031 7.12E−08 0.001637742 680649 Benzoic acid, 4-[2-(3,6-dioxo-1,4-cyclohexadienyl)- −0.642447826 7.15E−08 0.001644643 ethyl]-,methyl ester 678490 NA −0.633670084 7.17E−08 0.001649243 694465 NA −0.660753598 7.28E−08 0.001674546 625495 1-Piperidinecarbodithioic acid, antimony complex −0.633116158 7.42E−08 0.001706748 634784 4-Piperidinone, 1-[3-(dimethylamino)-1-oxopropyl]- −0.641843548 7.42E−08 0.001706748 3,5-bis(phenylmethylene)-, monohydrochloride 658365 NA −0.650885946 7.45E−08 0.001713649 680553 2-Quinoxalinecarboxylic acid, 3-[(4- 0.632426704 7.74E−08 0.001780355 fluorophenyl)amino]-, ethyl ester 723552 NA −0.632391437 7.76E−08 0.001784955 723548 NA −0.631797495 8.04E−08 0.001849361 650745 NA −0.679258766 8.07E−08 0.001856261 625501 Antimony, chlorobis(1-piperidinecarbodithioato-S,S′)- −0.631326045 8.28E−08 0.001904566 660638 NA −0.644161955 8.49E−08 0.00195287 740084 4-Carboxyl-benzo[b]thieno[17,16-d]-3-O-methyl- −0.634602557 8.83E−08 0.002031077 estra-1,3,5(10),16-tetraen-3-ol 681757 NA −0.638793028 8.95E−08 0.002058679 323241 3-Azabicyclo[3.2.2]nonane-3-carboselenoic acid, [1- −0.638458248 9.13E−08 0.002100083 (2-pyridinyl)ethylidene]hydrazide 676429 NA −0.62970674 9.14E−08 0.002102383 622700 Methanaminium, (2-oxo-1,3- −0.629497914 9.26E−08 0.002129985 cyclohexanediyl)bis(methyl)bis [N,N,N-trimethyl-, diiodide 715719 NA 0.647261212 9.29E−08 0.002136886 131238 NA −0.629334364 9.35E−08 0.002150687 681104 1,4,7,10-Tetraazacyclododecane-1,7- −0.629239243 9.41E−08 0.002164488 bis(methanephosphonicacid) 683326 NA −0.633221885 9.60E−08 0.002208192 715436 NA −0.628794739 9.66E−08 0.002221993 647472 NA −0.676216898 9.69E−08 0.002228894 9358 PADA, Pyridine-2-azodimethylaniline −0.632986428 9.74E−08 0.002240395 607320 NA −0.628664501 9.74E−08 0.002240395 246981 NA −0.632416098 1.01E−07 0.002323202 173905 Pentanamide, 2-(acetylamino)-N-[3-chloro-2-oxo-1- −0.632082775 1.03E−07 0.002369206 (phenylmethyl)propyl]-4-methyl- 309909 NIMBOLIDE −0.632098693 1.03E−07 0.002369206 668885 NA 0.636389583 1.03E−07 0.002369206 661224 NA −0.627244847 1.06E−07 0.002438212 681271 1,3,6-Triphenyl-oxazolo(5,4-d)pyrimidin-2′,4(1H,3H)- 0.627333988 1.06E−07 0.002438212 dion 650792 1,4,7,10-Tetrathia-13-azacyclopentadecane, 13-[(4- 0.627185177 1.07E−07 0.002461214 methylphenyl)sulfonyl]- 705163 NA −0.627092367 1.07E−07 0.002461214 637399 NA −0.627006549 1.08E−07 0.002484216 640355 NA −0.635693758 1.08E−07 0.002484216 668265 NA −0.635694004 1.08E−07 0.002484216 678503 1-Cyclobuten-3-one, 4,4-dichloro-1-pentyl- −0.626545825 1.11E−07 0.002553222 131233 Cyclopentanone, 2,5-bis[(dimethylamino)methyl]-, −0.634927797 1.13E−07 0.002599226 dihydrochloride 656599 NA −0.625789195 1.16E−07 0.002668232 641048 3,4′,4″,4″′-Tetrasulfonyl copper phthalocyanine, tetra −0.629934123 1.17E−07 0.002691234 sodium salt 677168 NA −0.625682634 1.17E−07 0.002691234 620514 1,4-Naphthalenedione, 7-(benzoyloxy)-5-methoxy- −0.625235185 1.20E−07 0.00276024 645740 NA 0.683316612 1.21E−07 0.002783242 717896 NA −0.625091031 1.21E−07 0.002783242 641395 1H-Benzo[a]carbazole-1,4(11H)-dione, 8-methoxy- −0.628928325 1.24E−07 0.002852248 130789 NA −0.624363897 1.26E−07 0.002898252 654379 ANTINEOPLASTIC-654379 −0.624401714 1.26E−07 0.002898252 677937 NA −0.624385863 1.26E−07 0.002898252 630708 Azacridoguanidine −0.68237738 1.27E−07 0.002921254 629974 7H-1,2,4-Triazolo[3,4-b][1,3,4]thiadiazine, 3-(4- −0.624033257 1.29E−07 0.002967258 chlorophenyl)-6-(5-nitro-2-furanyl)- 709468 NA −0.645997904 1.33E−07 0.003059266 637578 N-[3-(2-Pyridyl)isoquinolin-1-yl]-2- −0.623083451 1.36E−07 0.003128272 pyridinecarboxamidine 622460 NA −0.681190536 1.37E−07 0.003151274 637422 NA 0.665177697 1.37E−07 0.003151274 689185 NA −0.640731926 1.37E−07 0.003151274 106360 NA 0.640669699 1.38E−07 0.003174276 705162 NA −0.622909048 1.38E−07 0.003174276 678156 NA −0.622706786 1.39E−07 0.003197278 723001 Diethyl-N[4-(3-thienylquinoxalyn-2- 0.635529616 1.42E−07 0.003266284 yl)oxiphenylacetyl]-L-glutamate 639543 Cyclopentanone, 2-[(4-chlorophenyl)aminomethyl]-5- −0.62629817 1.45E−07 0.00333529 [(4-chlorophenyl)methylene]- 646160 NA −0.635088883 1.46E−07 0.003358292 625511 NA −0.663955843 1.47E−07 0.003381294 625496 NA −0.69107229 1.48E−07 0.003404296 638302 NA −0.663496442 1.51E−07 0.003473302 711861 NA −0.634532398 1.51E−07 0.003473302 684703 5,8-Quinolinedione, 2-chloro-6-methoxy-4-methyl-7- −0.621137739 1.53E−07 0.003519306 propyl- 292206 RUSTAIYAN A −0.625160256 1.55E−07 0.00356531 668259 NA −0.625120569 1.56E−07 0.003588312 668335 NA −0.620852014 1.56E−07 0.003588312 691415 NA 0.620438655 1.59E−07 0.003657318 742801 3-amino-N-(4-butoxyphenyl)-1H-indazole-1- −0.620330677 1.60E−07 0.00368032 carboxamide 684982 NA 0.63315698 1.64E−07 0.003772328 379546 NA −0.619836469 1.65E−07 0.00379533 626162 Discorhabdin C•TFA −0.619726061 1.66E−07 0.003818332 661440 5H-Benzocyclohepten-5-one, 6,7,8,9-tetrahydro-6- −0.619691759 1.67E−07 0.003841334 [(dimethylamino)methyl]-, hydrochloride 701663 NA −0.628204582 1.68E−07 0.003864336 657747 NA −0.661425358 1.70E−07 0.00391034 659754 NA 0.628009274 1.70E−07 0.00391034 713309 NA −0.656113103 1.73E−07 0.003979346 670341 NA −0.631705072 1.78E−07 0.004094356 638241 NA −0.618419911 1.79E−07 0.004117358 717518 NA −0.618225576 1.81E−07 0.004163362 666388 NA −0.618004813 1.84E−07 0.004232368 707827 NA −0.622156899 1.85E−07 0.00425537 668261 NA −0.621698553 1.90E−07 0.00437038 716688 NA 0.630514378 1.91E−07 0.004393382 710386 NA −0.621128737 1.97E−07 0.004531394 711074 NA −0.62545713 1.97E−07 0.004531394 92937 1H-Benzo[a]carbazole-1,4(11H)-dione, 11-methyl- −0.620925096 1.99E−07 0.004577398 685016 NA −0.625222241 2.00E−07 0.0046004 709438 NA −0.620521121 2.04E−07 0.004692408 619042 Cyclohexanone, 2,6-bis[(dimethylamino)methyl]-, −0.620080892 2.09E−07 0.004807418 dihydrochloride 669308 NA 0.628904571 2.10E−07 0.00483042 668264 NA −0.619602527 2.15E−07 0.00494543 310365 Na −0.615258346 2.16E−07 0.004968432 149286 1,4-Pentadien-3-one, 1,5-di-3-pyridyl- −0.615162113 2.17E−07 0.004991434 94889 Gardenin, Flavone, 5-hydroxy-3′,4′,5′,6,7,8- 0.623612432 2.20E−07 0.00506044 hexamethoxy- 618770 Piperidin-4-ol, N-ethyl-N-methyl-3-(1-oxo-3-phenyl- −0.623569755 2.20E−07 0.00506044 2-propen-1-yl)-4-(2-phenylethen-1-yl)-, (E,E)-, bromide 709483 NA −0.64685872 2.21E−07 0.005083442 382001 2-Propen-1-one, 2-[(dimethylamino)methyl]-1-(2,5- −0.618951658 2.23E−07 0.005129446 dimethyl phenyl)-, hydrochloride 618315 1,4-Naphthalenedione, 5-methoxy- −0.627510546 2.27E−07 0.005221454 715226 NA −0.618650914 2.27E−07 0.005221454 684424 Methyl 4-[2-[4-bromo-2,5- −0.614113457 2.30E−07 0.00529046 dihydroxyphenyl]ethyl]benzoate 640466 15-Ethoxynimbocinol −0.671985843 2.32E−07 0.005336464 620358 Methyl 13-hydroxy-15-oxo-kaurenoate −0.671890809 2.33E−07 0.005359466 736049 N-[2-(4-methoxyphenyl)-4-oxo-1,3-thiazolidin-3-yl]- 0.626940564 2.35E−07 0.00540547 N′-(2-methylimidazo[1,2-a]pyridin-3-yl)urea 620327 Carbonimidodithioic acid, [5-(4-nitrophenyl)-1,3,4- 0.617663697 2.40E−07 0.00552048 thiadiazol-2-yl]-, dimethyl ester 310342 Carbamimidothioic acid, [3-(4-chlorophenyl)-1,2,4- −0.621895705 2.42E−07 0.005566484 oxadiazol-5-yl]methyl ester, monohydrochloride 711830 NA −0.635491131 2.44E−07 0.005612488 714424 NA −0.621691132 2.45E−07 0.00563549 252844 SHIKONIN, Tokyo Violet −0.617302174 2.46E−07 0.005658492 668256 NA −0.617296362 2.46E−07 0.005658492 659288 NA −0.621378809 2.50E−07 0.0057505 711934 NA −0.617018974 2.50E−07 0.0057505 672041 NA −0.612352536 2.55E−07 0.00586551 712738 NA −0.63466292 2.55E−07 0.00586551 668325 NA −0.612238115 2.57E−07 0.005911514 682504 NA 0.612165578 2.58E−07 0.005934516 680551 NA 0.616154164 2.62E−07 0.006026524 690134 NA 0.611912293 2.62E−07 0.006026524 635449 Copper, chloro[2-[1-(2-pyridinyl)ethylidene][N,N- −0.61593769 2.65E−07 0.00609553 dipropyl-hydrazinecarbothioamidato-N,N,S]- 674068 NA −0.629093902 2.69E−07 0.006187538 710104 NA −0.624561292 2.69E−07 0.006187538 718306 NA 0.633722289 2.69E−07 0.006187538 636878 3-Methoxy-2-phenoxy-2-phenylimidazo[1,2- −0.65325807 2.71E−07 0.006233542 b]pyridazine 324979 Copper, chloro[hexahydro-1H-azepine-1-carbothioic −0.619883076 2.72E−07 0.006256544 acid[1-(2-pyridinyl)ethylidene]hydrazidato]-, (SP-4- 3)- 709882 Cirensenoxide G, Pulsatilloside C −0.611256814 2.72E−07 0.006256544 706192 NA −0.611187257 2.73E−07 0.006279546 715472 NA −0.615312348 2.75E−07 0.00632555 683260 NA −0.61526749 2.76E−07 0.006348552 715556 NA −0.624113833 2.76E−07 0.006348552 653624 NA −0.663261204 2.79E−07 0.006417558 659554 6-Bromo-3-bromomethyl-3,7-dichloro-7-methyl-1- −0.628244852 2.82E−07 0.006486564 octene 664303 Quinoline-2-ethanol, .alpha.,.alpha.- −0.610594963 2.82E−07 0.006486564 bis(trifluoromethyl)-, acetate (ester) 692405 NA −0.619044885 2.85E−07 0.00655557 669503 NA −0.610360963 2.86E−07 0.006578572 709928 NA 0.623421018 2.87E−07 0.006601574 657030 NA −0.610202701 2.88E−07 0.006624576 704212 NA 0.618889672 2.88E−07 0.006624576 640192 6-Phenylthio-7H-benzocycloheptene-1,4,7-trione −0.618558464 2.93E−07 0.006739586 677640 NA 0.609916098 2.93E−07 0.006739586 679092 NA 0.609732962 2.96E−07 0.006808592 706160 NA −0.641229625 3.03E−07 0.006969606 643726 NA −0.667098829 3.05E−07 0.00701561 661581 2-Azabicyclo[16.3.1]docosane, geldanamycin deriv. −0.609182881 3.06E−07 0.007038612 328416 Withaferin-A diacetate −0.613290735 3.09E−07 0.007107618 686368 Quinazolin-4(3H)-one, 3-ethyl-2-[[[5-(phenylamino)- 0.613192938 3.10E−07 0.00713062 1,3,4-thiadiazol-2-yl]methyl]thio]- 697223 NA −0.6408016 3.10E−07 0.00713062 687011 stereoisomer of 672120 (MW = 262) −0.617184002 3.17E−07 0.007291634 744075 NA −0.617186086 3.17E−07 0.007291634 36806 NA −0.608429405 3.19E−07 0.007337638 269121 DALBERGIONE −0.60840149 3.19E−07 0.007337638 620515 1,4-Naphthalenedione, 2-chloro-8-hydroxy-6- −0.61252676 3.22E−07 0.007406644 methoxy-7-methyl- 3907 Benzoic acid, 2-hydroxy-, compd. with 8-quinolinol −0.608205293 3.23E−07 0.007429646 (1:1) 747168 NA −0.608190859 3.23E−07 0.007429646 645633 NA −0.660474668 3.26E−07 0.007498652 690747 NA −0.621016008 3.28E−07 0.007544656 71297 Dihydrotomatidine −0.616518472 3.29E−07 0.007567658 659553 2,3,6-Tribromo-7-chloro-3,7-dimethyl-1-octene −0.616495519 3.29E−07 0.007567658 711811 NA −0.616452599 3.30E−07 0.00759066 704100 NA −0.607555312 3.35E−07 0.00770567 668263 NA −0.615548736 3.47E−07 0.007981694 641394 1H-Benzo[a]carbazole-1,4(11H)-dione, 11-phenyl- −0.611142543 3.48E−07 0.008004696 703776 NA −0.606842408 3.49E−07 0.008027698 687110 NA −0.615350495 3.51E−07 0.008073702 634473 NA 0.648393156 3.55E−07 0.00816571 656433 Pyrimidine-5-carboxylic acid, hexahydro-4-oxo-1,3- −0.628797162 3.55E−07 0.00816571 diphenyl-6-[2-[2-(piperidin-1-yl)ethyl]thio]-2-thioxo-, ethyl ester 709516 NA −0.610775393 3.55E−07 0.00816571 672042 NA −0.606500222 3.56E−07 0.008188712 648150 NA −0.606445169 3.57E−07 0.008211714 162062 Bicyclo[2.2.1]heptan-2-one, 3-[2-chloro-1- −0.610584265 3.59E−07 0.008257718 (chlorodifluoromethyl)-2,2-difluoroethylidene]- 622150 Violacene-1 −0.663971691 3.62E−07 0.008326724 712682 NA −0.62380367 3.62E−07 0.008326724 671363 2-Thiazolidinethione, 3-(4-fluorophenyl)-4,5- −0.606104047 3.64E−07 0.008372728 bis(phenylimino)- 699428 NA −0.61037114 3.64E−07 0.008372728 715748 NA 0.610004249 3.71E−07 0.008533742 678125 1H-indazole, 3-methoxy-1-[(2- 0.618682868 3.74E−07 0.008602748 methoxyphenyl)methyl]-5-nitro- 633207 NA −0.65782208 3.77E−07 0.008671754 638265 NA −0.647191416 3.80E−07 0.00874076 698148 NA −0.605309413 3.80E−07 0.00874076 659390 NA −0.605247653 3.81E−07 0.008763762 685918 NA −0.609540666 3.81E−07 0.008763762 713690 NA −0.64185064 3.85E−07 0.00885577 671379 NA 0.605056403 3.86E−07 0.008878772 302979 Shikoccin, Isodon Shikokianus compound A −0.604920158 3.88E−07 0.008924776 686130 Acetamide, N-[6′-(diethylamino)-3-oxospiro- −0.604880228 3.89E−07 0.008947778 [isobenzofuran-1(3H),9′-[9H]xanthen]-2′-yl]-N- phenyl- 704565 NA −0.609113351 3.90E−07 0.00897078 693813 NA −0.608723565 3.99E−07 0.009177798 704970 NA −0.641020396 4.03E−07 0.009269806 711824 NA −0.612822741 4.04E−07 0.009292808 677268 NA −0.651006745 4.09E−07 0.009407818 3927 Thiolutin, Acetopyrrothin −0.603917571 4.11E−07 0.009453822 618560 NA 0.650868305 4.12E−07 0.009476824 712571 Artesunate, Dihydroqinghaosusuccinate −0.626057056 4.13E−07 0.009499826 625814 NA −0.656056228 4.15E−07 0.00954583 639387 NA −0.667005018 4.16E−07 0.009568832 625502 4-Morpholinecarbodithioic acid, antimony complex −0.603480214 4.21E−07 0.009683842 626161 2-Hydroxy discorhabdin D −0.672112363 4.29E−07 0.009867858

Example 2 Gene Expression Data Reveal Common Pathways that Characterize the Unifocal Nature of Ovarian Cancer Materials and Methods

Pelvic OVCA samples and matched, nonconfluent, extrapelvic implants were obtained from 30 patients who had provided written informed consent to the Moffitt Cancer Center Institutional Total Cancer Care (TCC) protocol, prior to undergoing primary cytoreductive surgery for advanced stage serous epithelial OVCA. The study was carried out with approval from the University of South Florida Institutional Review Board.

A pelvic sample was resected from the ovarian tissue, which, in the opinion of the surgeon, most likely represented the primary site in the pelvis. From each patient, a matched, nonconfluent extrapelvic implant was identified and collected. Samples were flash frozen in liquid nitrogen within 10 minutes of surgical resection and stored at −80° C. A histopathological review was performed to confirm the diagnosis, and samples were macrodissected to ensure greater than 70% tumor content. Total RNA and genomic DNA were extracted from each sample.

Normal ovarian surface epithelium (NOSE) samples were obtained from patients who had provided written informed consent to the TCC protocol and had undergone oophorectomy at the Moffitt Cancer Center for nonmalignant disease, not associated with the ovary. Immediately after surgical resection, the surface epithelium was gently scraped from the surface and immediately subjected to RNA isolation. To ensure sufficient quantities of RNA, NOSE RNA samples were pooled in groups of 3 or 4 to produce a minimum RNA quantity of 50 ng. As a result of such pooling, 49 normal ovaries were analyzed on 12 Affymetrix Gene-Chip assays (Santa Clara, Calif.).

Approximately 30 mg of tissue was used for each RNA and DNA extraction. Tissues were pulverized in BioPulverizer H tubes (Bio101) using a Mini-Beadbeater (Biospec Products, Bartlesville, Okla.). Total RNA was collected using the QIAGEN RNeasy minikit (Valencia, Calif.) according to the manufacturer's instructions. RNA quality was checked on an Agilent Bioanalyzer (Palo Alto, Calif.) to assess the quality of RNA via the 28S:18S ribosomal RNAs. Genomic DNA was isolated using the QIAGEN QIAamp® DNA minikit according to the manufacturer's instructions. For microarray analysis, 10 mg of total RNA was used to develop the targets for Affymetrix microarray analysis, and probes were prepared according to the manufacturer's instructions. Briefly, biotin-labeled complementary RNA was produced by in vitro transcription, fragmented, and hybridized to the customized human Affymetrix HuRSTA gene chips (HuRSTA-2a520709). Expression values were calculated using the robust multiarray average algorithm implemented in Bioconductor extensions to the R statistical programming environment.

A Student t test was used to identify differentially expressed genes in comparisons among NOSE, pelvic, and extrapelvic sample genomic data. For each comparison, the 12 NOSE samples were grouped together. Pelvic and extrapelvic genomic profiles were analyzed as groups (pelvic as one group, extrapelvic as another) and as individual pairs (comparisons of matched pelvic/extrapelvic pairs from the same patient). As such, the following comparisons were made: (1) grouped NOSE vs grouped pelvic implants, (2) grouped NOSE vs grouped extrapelvic implants, (3) grouped pelvic vs grouped extrapelvic implant, (4) grouped NOSE vs individual pelvic implants, (5) grouped NOSE vs individual extrapelvic implants, and (6) individual pelvic vs individual matched extrapelvic samples from the same patient. For each of the comparisons, differentially expressed genes were analyzed using MetaCore™ software (GeneGO, St Joseph, Mich.) to identify represented biological pathways.

Identified pathways were further evaluated for differential representation in 4 publically available gene expression datasets encompassing 389 patient samples including: (1) OVCA (n=12; 4 early- and 8 advanced-stage), GEO accession number GSE14407, U133Plus gene chip; (2) oral cancer (n=27; 22 primary lesions, 5 metastases), GEO accession GSE2280, U133A gene chip; (3) prostate cancer (n=271; 196 primary lesions, 75 metastases), GEO accession GSE6919, U95 gene chip; and (4) prostate cancer (n=79; 40 nonrecurrent, 39 recurrent lesions), GEO accession GSE25136, U133A gene chip (by Student t test, gene cutoff P<0.01).

Principal component analysis (PCA) was performed using Evince software. Logrank tests were used to test associations between pathway expression (using a median PCA score value cutoff) and overall survival within 9 publically available datasets comprising 1691 patient samples, including cancers of the ovary, which included 4 datasets (Australian dataset [n=218 GSE9891], 3 Moffitt Cancer Center (MCC) dataset [n=142], 4 MD Anderson dataset [n=53 GSE18520], and The Cancer Genome Atlas (TCGA) dataset [n=497]) as well as brain (n=182 GSE13041), 5 breast (n=187 GSE2990), colon (n=177 GSE17538), 6 lung (n=58 TCGA), and blood (leukemia, n=182 TCGA). All survival analyses were performed using the R program.

For sequence analysis of p53, exons 5-8 of p53 from primary lesions and distal metastases separated by noninvolved tissue were analyzed for primary sequence mutation patterns. Genomic DNA (100 ng) was used in PCR amplification reactions essentially as described previously (Leonard D G, et al. Clin Cancer Res 2002 8:973-85) using the following primers:

exon 5, sense (SEQ ID NO: 1) 5′-TTCCTCTTCCTACAGTACTC-3′, antisense (SEQ ID NO: 2) 5′-GCAACCAGCCCTGTCGTCTC-3′; exon 6, sense (SEQ ID NO: 3) 5′-ACCATGAGCGCTGCTCAGAT-3′, antisense (SEQ ID NO: 4) 5′-AGTTGCAAACCAGACGTCAG-3′; exon 7, sense (SEQ ID NO: 5) 5′-GTGTTGTCTCCTAGGTTCGC-3′, antisense (SEQ ID NO: 6) 5′-CAAGTGGCTCCTGACCTGGA-3′; and exon 8, sense (SEQ ID NO: 7) 5′-CCTATCCTGAGTAGTGGTAA-3′, antisense (SEQ ID NO: 8) 5′-TGAATCTGAGGCATAACTGC-3′.

Amplifications were performed using an Eppendorf Mastercycler® thermocycler in 50 mL reaction volumes (100 ng genomic DNA, 1 U Taq DNA polymerase [Invitrogen, Carlsbad, Calif.], 1.5 mM MgCl2, 0.2 mM deoxynucleotide triphosphates, and 0.2 mM primer mix) by standard protocols. Briefly, samples were held at 95° C. for 10 minutes followed by 30 cycles of the following: 95° C. for 50 seconds, annealing temperature at 56° C. or 60° C., depending on the primers, for 90 seconds, and an elongation step at 72° C. for 90 seconds. After cycling, samples were held at 72° C. for 10 minutes and cooled to 4° C. PCR products were purified using the Purelink® PCR purification kit (QIAGEN) and evaluated using 4% agarose gels. Sequencing was performed on an Applied Biosystem's AB3130 genetic analysis system using BigDye® 3.1 dye terminator chemistry (Applera, Applied Biosystems, Foster City, Calif.) according to the manufacturer's instructions. Comparative sequence analysis of p53 exons was performed using Lasergene® 8 software (DNAStar, Madison, Wis.).

The effects of pathway inhibition on OVCA cell metastatic properties were investigated using the in vitro scratch assay. HeyA8 OVCA cells were maintained in RPMI 1640 medium (Invitrogen) supplemented with 10% fetal bovine serum (FBS; Fisher Scientific, Pittsburgh, Pa.), 1% sodiumpyruvate, 1% penicillin/streptomycin (Cellgro, Manassas, Va.), and 1% nonessential amino acids (HyClone, Hudson, N.H.). Monolayers, 75-80% confluent, were cultured in serum-free media for 4 hours and then mechanically disrupted to create a wound using a 1 mL pipette tip. Culture plates were washed twice with serum-free media to remove floating cells and then incubated with media containing 10% FBS and either vehicle (dimethylsulfoxide [DMSO]) or drug. The DMSO concentration was maintained below 0.5% so as not to influence cell growth or migration. The underside of the culture plate by the wound area was marked with a Sharpie for reference, and wounds were imaged by phase-contrast microscopy on days 0, 1, and 2.

Results

Comparison of Overall Expression Patterns

PCA modeling was used to assess the overall similarities in gene expression among NOSE, pelvic, and extrapelvic samples. PCA generates a set of vectors (termed first principal component [PC1], second principal component [PC2], etc) that summarize the overall genome-wide expression patterns for a sample. Each principal component provides a summary measure for genes that share certain expression characteristics. Comparing PCA values enables a global assessment of how similar or different samples are at a genome-wide level. The 2 first principal components for all samples are shown in FIG. 1. PC1, which explained 35.4% of the variation, separated most of the NOSE samples from the primary pelvic and the extrapelvic samples.

Comparison of Pathway Expression in NOSE, Pelvic, and Extrapelvic OVCAs

Grouped comparisons of NOSE, pelvic, and extrapelvic genomic data was performed. At a significance of P<0.01 (Bonferroni adjusted), 970 probe sets representing 71 signaling pathways (P<0.05) were identified when the grouped NOSE expression data were compared with the grouped primary pelvic sample data, and 1075 probe sets representing 143 signaling pathways were identified when the grouped NOSE expression data were compared with the grouped extrapelvic implant expression data (Table 15). Importantly, the 60 of 71 signaling pathways (85%) present in primary pelvic samples were also represented in extrapelvic implants. At this level of significance, no probe sets were found to be differentially expressed between the grouped primary pelvic and extrapelvic samples.

When the grouped NOSE dataset was analyzed against the individual pelvic primary samples (n=30) and the individual extrapelvic implants (n=30), an average of 7392 and 7772 probe sets, respectively, demonstrated differential expression (greater than 2-fold). In contrast, an average of 1463 probe sets was differentially expressed between individual pelvic and matched extrapelvic implants from the same patient. Consistently, these data suggest significant similarity between the primary pelvic and matched extrapelvic implants (Table 10).

TABLE 10 Number of probe sets with greater than 2-fold change in expression Normal ovary vs Normal ovary vs Pelvic primary vs Sample pelvic primary extrapelvic implant extrapelvic implant 1 6339 8137 2413 2 6562 7483 2813 3 6873 6608 3464 4 7049 7069 1032 5 8012 6834 1710 6 8052 7304 2446 7 8364 7951 335 8 6645 6886 6220 9 7229 7343 86 10 8469 7497 2048 11 8069 7980 2151 12 8321 8192 596 13 7944 7867 683 14 8080 8836 1135 15 7157 8225 1120 16 7249 7105 874 17 7171 7682 600 18 7424 7907 660 19 7754 8244 545 20 8342 8130 980 21 6790 8024 138 22 7341 7620 2020 23 6876 8007 925 24 6728 8127 3449 25 8144 7833 600 26 7717 7888 545 27 7539 6968 1630 28 6965 7629 620 29 6793 9087 850 30 5749 8706 1213 31 6304 6878 4084 Mean 7356 7743 1548

Mutational Analysis of p53

Exons 5-8 of the p53 gene were examined in primary pelvic and matched extrapelvic implants (Table 11). A total of 13 nucleotide mutations were found in 11 of 30 primary pelvic samples. A mutation in exon 5 was found in 1 primary pelvic, whereas 3 primary pelvic lesions had a mutation in exon 6, 7 pelvic lesions had a mutation in exon 7, and 2 pelvic lesions had a mutation in exon 8. The majority of identified mutations were missense (9 of 13); however, 1 sample showed a frame shift mutation resulting from a deletion in codon 151 of exon 5, 1 sample showed a nonsense mutation in codon 294 of exon 8, and 2 samples displayed silent mutations. In every case, the p53 mutation identified in the primary pelvic was also present in the matched extrapelvic implant.

TABLE 11 Primary sequence mutations in p53 exons 5-8 p53 mutation in primary ovarian cancer Primary Amino acid Histological type Grade Stage site Exon Codon change Serous adenocarcinoma High 3C Rt ovary WT WT WT Serous adenocarcinoma High 4 Rt ovary 6 220, Tyr to Cys TAT to TGT 7 225, Val to Val GTT to GTG Serous adenocarcinoma High 3C Lt ovary WT WT WT Serous adenocarcinoma High 3C Rt ovary 8 294, Glu to STOP GAG to TAG Serous adenocarcinoma High 3C Lt ovary WT WT WT Adenocarcinoma with High 4 Lt ovary WT WT WT papillary features Adenocarcinoma with High 3C Lt ovary 7 248, Arg to Gln papillary features CGG to CAG Serous adenocarcinoma High 3C Rt ovary 7 248, Arg to Gln CGG to CAG Serous adenocarcinoma High 4 Rt ovary WT WT WT Adenocarcinoma High 3C Rt ovary WT WT WT Adenocarcinoma with Not 3C Lt ovary WT WT WT papillary features given Serous adenocarcinoma High 3C Lt ovary WT WT WT Adenocarcinoma with High 2B Rt ovary 6 220, Tyr to Cys papillary features TAT to TGT Clear cell carcinoma High 3C Lt ovary WT WT WT Adenocarcinoma with High 3C Lt ovary 7 245, Gly to Asp papillary features GGC to GAC Adenocarcinoma with High 3C Rt ovary 7 248, Arg to Gln papillary features CGG to CAG Adenocarcinoma High 3C Lt ovary WT WT WT Serous adenocarcinoma High 3C Rt ovary WT WT WT Serous adenocarcinoma High 3C Rt ovary WT WT WT Serous adenocarcinoma High 4 Rt ovary WT WT WT Adenocarcinoma High 2C Rt ovary WT WT WT Adenocarcinoma High 3C Rt ovary WT WT WT Adenocarcinoma with High 4 Rt ovary WT WT WT papillary features Serous adenocarcinoma High 3C Rt ovary 7 234, Tyr to Cys TAC to TGC Serous adenocarcinoma High 3C Rt, Lt ovary WT WT WT Adenocarcinoma High 3C Rt ovary 5 151, Pro to frame CCC to {hacek over ( )}CC shift Adenocarcinoma High 3B Rt, Lt ovary WT WT WT Serous adenocarcinoma Moderate 3C Rt ovary WT WT WT Serous adenocarcinoma High 3C Rt, Lt ovary 8 282, Asp to Trp CGG to TGG Clear cell carcinoma High 3C Lt ovary 6 213, Arg to Arg CGA to CGG 7 245, Gly to Asp GGC to GAC p53 mutation in extrapelvic implants Extrapelvic Amino acid Histological type Grade Stage site Exon Codon change Serous adenocarcinoma High 3C Omentum WT WT WT Serous adenocarcinoma High 4 6 220, Tyr to Cys TAT to TGT 7 225, Val to Val GTT to GTG Serous adenocarcinoma High 3C Omentum WT WT WT Serous adenocarcinoma High 3C Soft tissue, 8 294, Glu to STOP pelvis GAG to TAG Serous adenocarcinoma High 3C Omentum WT WT WT Adenocarcinoma with High 4 Omentum WT WT WT papillary features Adenocarcinoma with High 3C Omentum 7 248, Arg to Gln papillary features CGG to CAG Serous adenocarcinoma High 3C Omentum 7 248, Arg to Gln CGG to CAG Serous adenocarcinoma High 4 Colon WT WT WT Adenocarcinoma High 3C Omentum WT WT WT Adenocarcinoma with Not 3C Omentum WT WT WT papillary features given Serous adenocarcinoma High 3C Omentum WT WT WT Adenocarcinoma with High 2B Cul-de-sac 6 220, Tyr to Cys papillary features TAT to TGT Clear cell carcinoma High 3C Omentum WT WT WT Adenocarcinoma with High 3C Omentum 7 245, Gly to Asp papillary features GGC to GAC Adenocarcinoma with High 3C Omentum 7 248, Arg to Gln papillary features CGG to CAG Adenocarcinoma High 3C Colon WT WT WT Serous adenocarcinoma High 3C Omentum WT WT WT Serous adenocarcinoma High 3C Omentum WT WT WT Serous adenocarcinoma High 4 Omentum WT WT WT Adenocarcinoma High 2C Omentum WT WT WT Adenocarcinoma High 3C Omentum WT WT WT Adenocarcinoma with High 4 Omentum WT WT WT papillary features Serous adenocarcinoma High 3C Omentum 7 234, Tyr to Cys TAC to TGC Serous adenocarcinoma High 3C Omentum WT WT WT Adenocarcinoma High 3C Omentum 5 151, Pro to frame CCC to {hacek over ( )}CC shift Adenocarcinoma High 3B Omentum WT WT WT Serous adenocarcinoma Moderate 3C Soft tissue WT WT WT (periaortic) Serous adenocarcinoma High 3C Omentum 8 282, Asp to Trp CGG to TGG Clear cell carcinoma High 3C Omentum 6 213, Arg to Arg CGA to CGG 7 245, Gly to Asp GGC to GAC

Pathways Associated with Metastasis Influence Clinical Outcome

Experiments were conducted to identify pathways present in extrapelvic samples that were not present in pelvic samples (termed candidate metastasis pathways [CMPs]). 2 statistical approaches were adopted: comparisons of data grouped together and individual patient-matched samples. Five CMPs demonstrated differential expression using both approaches; that is, they were present in extrapelvic samples but not in pelvic samples when data were compared both in grouped analyses (81 total pathways; Table 12) and in 15 or more of 30 (50%) of the patients for whom individual comparisons were made between matched pelvic and extrapelvic samples (24 pathways total; Table 13).

TABLE 12 Grouped analysis: pathways unique to grouped NOSE vs grouped extrapelvic implants FDR less Pathway name than 0.05? P value 1 Immune response, immunological synapse formation Yes 9.08E−05 2 Apoptosis and survival, role of IAP proteins in apoptosis Yes 3.69E−04 3 Oxidative stress, angiotensin II-induced production of ROS Yes 7.31E−04 4 Development, mu-type opioid receptor signaling via beta-arrestin Yes 8.11E−04 5 Development, activation of ERK by kappa-type opioid receptor Yes 8.54E−04 6 Immune response, histamine signaling in dendritic cells Yes 9.43E−04 7 Glutathione metabolism/rodent version No 3.01E−02 8 Signal transduction, JNK pathway Yes 1.96E−03 9 Immune response, delta-type opioid receptor signaling in T cells Yes 1.99E−03 10 Immune response, NF-AT signaling and leukocyte interactions No 3.15E−03 11 Immune response, IL-15 signaling No 4.02E−03 12 Chemotaxis, inhibitory action of lipoxins on IL-8- and leukotriene B4- No 5.31E−03 induced neutrophil migration 13 Immune response, PGE2 common pathways No 5.84E−03 14 Immune response, IFN alpha/beta signaling pathway No 6.44E−03 15 Apoptosis and survival, apoptotic activin A signaling No 7.47E−03 16 Cytoskeleton remodeling, TGF, WNT and cytoskeletal remodeling No 8.71E−03 17 Inhibitory action of lipoxins on neutrophil migration No 9.13E−03 18 Immune response, CCR5 signaling in macrophages and T lymphocytes No 9.92E−03 19 Immune response, neurotensin-induced activation of IL-8 in No 1.02E−02 colonocytes 20 Neurophysiological process, HTR1A receptor signaling in neuronal No 1.02E−02 cells 21 Regulation of lipid metabolism, G-alpha(q) regulation of lipid No 1.08E−02 metabolism 22 Apoptosis and survival, FAS signaling cascades No 1.12E−02 23 Development, angiotensin signaling via PYK2 No 1.12E−02 24 G-protein signaling, RhoB regulation pathway No 1.31E−02 25 Development, ligand-independent activation of ESR1 and ESR2 No 1.36E−02 26 Immune response, PGE2 signaling in immune response No 1.36E−02 27 Development, gastrin in cell growth and proliferation No 1.36E−02 28 Cell adhesion, chemokines, and adhesion No 1.41E−02 29 Development, G-CSF-induced myeloid differentiation No 1.43E−02 30 Development, G proteins mediated regulation MAPK-ERK signaling No 1.48E−02 31 Transcription, transcription factor Tubby signaling pathways No 1.56E−02 32 Development, beta-adrenergic receptors regulation of ERK No 1.62E−02 33 Immune response, Fc gamma R-mediated phagocytosis in macrophages No 1.62E−02 34 Cell adhesion, integrin-mediated cell adhesion, and migration No 1.76E−02 35 Signal transduction, ERK1/2 signaling pathway No 1.79E−02 36 Development, A3 receptor signaling No 1.91E−02 37 Development, G-CSF signaling No 1.91E−02 38 Development, angiotensin activation of ERK No 1.98E−02 39 Apoptosis and survival, caspase cascade No 1.98E−02 40 Cell adhesion, IL-8-dependent cell migration and adhesion No 1.98E−02 41 Neurophysiological process, corticoliberin signaling via CRHR1 No 2.07E−02 42 Protein folding, membrane trafficking, and signal transduction of G- No 2.11E−02 alpha (i) heterotrimeric G protein 43 G protein signaling, G protein beta/gamma signaling cascades No 2.19E−02 44 Immune response, role of the membrane attack complex in cell survival No 2.19E−02 45 G protein signaling, G protein alpha-q signaling cascades No 2.19E−02 46 Signal transduction, activation of PKC via G protein coupled receptor No 2.41E−02 47 Development, FGF family signaling No 2.41E−02 48 G protein signaling, proinsulin C-peptide signaling No 2.41E−02 49 Immune response, antiviral actions of interferons No 2.41E−02 50 Development, EPO-induced Jak-STAT pathway No 2.42E−02 51 Immune response, inflammasome in inflammatory response No 2.42E−02 52 Immune response, oncostatin M signaling via MAPK in mouse cells No 2.42E−02 53 G protein signaling, S1P2 receptor signaling No 2.42E−02 54 Cell cycle, influence of Ras and Rho proteins on G1/S transition No 2.60E−02 55 Immune response, IL-9 signaling pathway No 2.65E−02 56 G protein signaling, Rac2 regulation pathway No 2.65E−02 57 Immune response, TLR signaling pathways No 2.79E−02 58 Immune response, oncostatin M signaling via MAPK in human cells No 2.90E−02 59 Development, S1P4 receptor signaling pathway No 3.13E−02 60 Immune response, MIF-mediated glucocorticoid regulation No 3.13E−02 61 Immune response, role of integrins in NK cells cytotoxicity No 3.16E−02 62 Immune response, human NKG2D signaling No 3.16E−02 63 Cell adhesion, integrin inside-out signaling No 3.20E−02 64 G protein signaling, regulation of p38 and JNK signaling mediated by G No 3.44E−02 proteins 65 Apoptosis and survival, ceramide signaling pathway No 3.73E−02 66 Immune response, Th1 and Th2 cell differentiation No 3.73E−02 67 Development, dopamine D2 receptor transactivation of EGFR No 3.93E−02 68 Development, VEGF family signaling No 4.04E−02 69 Neurophysiological process, NMDA-dependent postsynaptic long-term No 4.15E−02 potentiation in CA1 hippocampal neurons 70 Serotonin modulation of dopamine release in nicotine addiction No 4.35E−02 71 Apoptosis and survival, lymphotoxin-beta receptor signaling No 4.35E−02 72 Immune response, murine NKG2D signaling No 4.35E−02 73 Development, angiotensin signaling via beta-arrestin No 4.37E−02 74 Development, alpha-2 adrenergic receptor activation of ERK No 4.67E−02 75 Development, ACM2 and ACM4 activation of ERK No 4.68E−02 76 Signal transduction, AKT signaling No 4.68E−02 77 Immune response, IL-7 signaling in B lymphocytes No 4.68E−02 78 Development, S1P3 receptor signaling pathway No 4.68E−02 79 Signal transduction, AKT signaling No 4.68E−02 80 Immune response, HTR2A-induced activation of cPLA2 No 4.68E−02 81 G protein signaling, Ras family GTPases in kinase cascades (scheme) No 4.83E−02 ACM, muscarinic acetylcholine receptor; CCR, chemokine receptor; cPLA, cytosolic phospholipase A; CRHR, corticotropin releasing hormone receptor; EGFR, epithelial growth factor receptor; EPO, erythropoietin; ERK, extracellularly regulated kinase; ESR1, estrogen receptor-[alpha] gene; ESR2, estrogen receptor-[beta] gene; FAS, fatty acid synthase; FDR, false discovery rate; FGF, fibroblast growth factor; G-CSF, granulocyte colony-stimulating factor; GTP, guanosine triphosphate; HTR, hydroxytryptane receptor; IAP, integrin-associated protein; IL, interleukin; IFN, interferon; Jak, Janus kinase; JNK, c-Jun N-terminal kinase; MAPK, mitogen-activated protein kinase; MIF, migration inhibitor factor; NF-AT, nuclear factor of activated T cells; NK, natural killer; NMDA, N-methyl-Daspartate; NOSE, normal ovarian surface epithelium; PG, prostaglandin; PKC, protein kinase C; PYK, proline-rich tyrosine kinase; ROS, reactive oxygen species; S1P, sphingosine 1-phosphate; STAT, signal transducer and activator of transcription; VEGF, vascular endothelial growth factor.

TABLE 13 Individual primary pelvic (n = 30) vs extrapelvic implant (n = 30) Common to Pathway name number pairs 1 Cell adhesion, ECM remodeling 27 2 CXC chemokine receptor family 25 3 Cell adhesion, cell matrix glycoconjugates 23 4 Cell adhesion, chemokines and adhesion 23 5 Development, regulation of EMT 23 6 Development, Hedgehog, and PTH signaling pathways 20 in bone and cartilage development 7 Role of diethylhexyl phthalate and tributyltin in 20 fat cell differentiation 8 Development, beta-adrenergic receptors signaling 18 via cAMP 9 Immune response, IL-17 signaling pathways 18 10 Protein folding, membrane trafficking, and signal 18 transduction of G-alpha (i) heterotrimeric G protein 11 Cardiac hypertrophy, NF-AT signaling in cardiac 17 hypertrophy 12 Cell adhesion, plasmin signaling 17 13 Development, TGF-betaedependent induction of EMT 17 via SMADs 14 Development, WNT signaling pathway, part 2 17 15 Immune response, histamine H1 receptor signaling 17 in immune response 16 Cytoskeleton remodeling, TGF, WNT, and 16 cytoskeletal remodeling 17 Development, role of activin A in cell differentiation 16 and proliferation 18 Development, TGF-betaedependent induction of EMT 16 via MAPK 19 Immune response, HMGB1/RAGE signaling pathway 16 20 PGE2 pathways in cancer 16 21 Chemotaxis, leukocyte chemotaxis 15 22 Immune response, histamine signaling in dendritic 15 cells 23 Immune response, MIF-mediated glucocorticoid 15 regulation 24 Immune response, TLR signaling pathways 15 Pathways are common to more than 15 paired samples. cAMP, cyclic adenosine diphosphate; ECM, extracellular matrix; EMT, epithelial-to-mesenchymal transition; HMGB, high mobility group protein B; IL, interleukin; MAPK, mitogen-activated protein kinase; MIF, migration inhibitor factor; NF-AT, nuclear factor of activated T cells; PG, prostaglandin; PTH, parathyroid hormone; RAGE, receptor for advanced glycation end products; SMAD, phosphorylated mothers against decapentaplegic.

These 5 CMPs included the following: (1) chemokines and cell adhesion (chemokines/cell adhesion pathway), (2) transforming growth factor (TGF)-beta and cytoskeletal remodeling (TGF-WNT/cytoskeleton remodeling pathway), (3) histamine signaling in dendritic cells and immune response (histamine signaling/immune response pathway), (4) Toll-like receptor (TLR) signaling pathways and immune response (TLR pathway), and (5) protein folding, membrane trafficking, and signal transduction of G-alpha (i) heterotrimeric G-protein (G-alpha pathway).

To further explore the validity of these 5 CMPs, each were evaluated in 4 publically available external gene expression datasets from primary or early-stage cancers vs metastatic/advanced or recurrent cancer. Pathways associated with metastatic, advanced-stage, or recurrent disease included the following: (1) TGF-WNT/cytoskeleton remodeling pathway (P<0.0001) and chemokines/cell adhesion pathway (P<0.001) for ovarian cancer (GSE14407); (2) TGF-WNT/cytoskeleton remodeling (P<0.001) for oral cavity (GSE2280); and (3) TGF-WNT/cytoskeleton remodeling (GSE6919; P<0.001), chemokines/cell adhesion (GSE6919; P<0.001), histamine signaling/immune response (GSE6919; P=0.016), TGF-WNT/cytoskeleton remodeling (GSE6919; P<0.001), and chemokines/cell adhesion (GSE6919; P<0.001) for prostate cancer. Based on their representation in the external datasets, TGF-WNT/cytoskeleton remodeling, chemokines/cell adhesion, and histamine signaling/immune response pathways were defined as metastasis pathways from the initial list of 5 CMPs.

To further explore the clinical relevance of the 3 metastasis pathways, associations (log-rank P values) were evaluated between pathway expression (quantified by PCA modeling) and overall survival in 1691 patients from a series of 9 external clinicogenomic datasets. Genes included in the PC1 signature scores for the TGF-WNT/cytoskeleton remodeling, chemokines/cell adhesion, and histamine signaling/immune response pathways are listed in Table 14.

TABLE 14 Genes used for PCA modeling from the TGF-WNT/cytoskeleton remodeling, chemokines/cell adhesion, and histamine signaling/immune response pathways. Histamine- TGF-WNT Chemokines Dendritic ACTA1 LRP5 TSC2 ACTA1 HRAS ADCY1 ACTA2 MAP2K1 VAV1 ACTA2 IL8 ADCY2 ACTB MAP2K2 VCL ACTB ILK ADCY3 ACTC1 MAP2K3 VEGFA ACTC1 ITGA11 ADCY4 ACTG1 MAP3K11 VTN ACTG1 ITGA3 ADCY5 ACTG2 MAP3K7 WASL ACTG2 ITGA6 ADCY6 ACTN1 MAPK1 WIF1 ACTN1 ITGA8 ADCY7 ACTN2 MAPK11 WNT1 ACTN2 ITGAV ADCY8 ACTN3 MAPK12 WNT10A ACTN3 ITGB1 ADCY9 ACTN4 MAPK13 WNT10B ACTN4 ITGB4 CCL2 ACTR2 MAPK14 WNT11 ACTR2 JUN CCL5 ACTR3 MAPK3 WNT16 ACTR3 KDR CD86 ACTR3B MDM2 WNT2 ACTR3B LAMA1 CREB1 AKT1 MKNK1 WNT2B AKT1 LAMA4 CREM AKT2 MMP13 WNT3 AKT2 LAMB1 MAPK3 AKT3 MMP7 WNT3A AKT3 LAMC1 MAPK1 ARPC1A MTOR WNT4 ARPC1A LEF1 GNAI1 ARPC1B MYC WNT5A ARPC1B LIMK1 GNAI2 ARPC2 MYL1 WNT5B ARPC2 LIMK2 GNAI3 ARPC3 MYL12A WNT6 ARPC3 MAP2K1 GNAO1 ARPC4 MYL12B WNT7A ARPC4 MAP2K2 GNAZ ARPC5 MYL2 WNT7B ARPC5 MAPK1 GNA11 AXIN1 MYL3 WNT8A BCAR1 MAPK3 GNAQ AXIN2 MYL4 WNT8B BRAF MMP1 GNAS BCAR1 MYL5 WNT9A CAV1 MMP13 GNB1 CASP9 MYL6 WNT9B CAV2 MMP2 GNB2 CAV1 MYL6B XIAP CCL2 MSN GNB3 CCND1 MYL7 ZFYVE9 CCR1 MYC GNB4 CDC42 MYL9 CD44 NFKB1 GNB5 CDKN1A MYLK CD47 NFKB2 GNG10 CDKN2B MYLK2 CDC42 PAK1 GNG11 CFL1 MYLK3 CFL1 PIK3CA GNG12 CFL2 MYLPF CFL2 PIK3CB GNG13 CHUK NCL COL1A1 PIK3CD GNG2 COL4A1 NLK COL1A2 PIK3CG GNG3 COL4A2 PAK1 COL4A1 PIK3R1 GNG4 COL4A3 PIK3CA COL4A2 PIK3R2 GNG5 COL4A4 PIK3CB COL4A3 PIK3R3 GNG7 COL4A5 PIK3CD COL4A4 PIK3R5 GNG8 COL4A6 PIK3R1 COL4A5 PIP5K1C GNGT1 CRK PIK3R2 COL4A6 PLAT GNGT2 CSNK2A1 PIK3R3 CRK PLAU HRH1 CSNK2A2 PLAT CTNNB1 PLAUR HRH2 CSNK2B PLAU CXCL1 PLG HRH3 CTNNB1 PLAUR CXCL5 PTEN HRH4 DOCK1 PLG CXCL6 PTK2 IL1B DSTN PPARD CXCR1 PXN IL10 DVL1 PPP1CB CXCR2 RAC1 IL12A DVL2 PPP1R12A DBN1 RAF1 IL12B DVL3 PTK2 DOCK1 RAP1A IL23A EIF4E PXN FLNA RAP1GAP IL6 EIF4EBP1 RAC1 FLOT2 REL IL8 FN1 RAF1 FN1 RELA ITPR1 FOXO3 RHEB GNAI1 RELB ITPR2 FRAT1 RHOA GNAI2 RHOA ITPR3 FZD1 ROCK1 GNAI3 ROCK1 IRF8 FZD10 ROCK2 GNAO1 ROCK2 MAP2K1 FZD2 RPS6KA5 GNAZ SDC2 MAP2K2 FZD3 SERPINE1 GNB1 SERPINE1 CCL3 FZD4 SERPING1 GNB2 SERPINE2 CCL4 FZD5 SHC1 GNB3 SHC1 NFATC2 FZD6 SMAD2 GNB4 SOS1 NFATC1 FZD7 SMAD3 GNB5 SOS2 PRKACA FZD8 SOS1 GNG10 SRC PRKACB FZD9 SOS2 GNG11 TCF7 PRKACG GRB2 SP1 GNG12 TCF7L1 PRKAR1A GSK3B SRC GNG13 TCF7L2 PRKAR1B HRAS TAB1 GNG2 THBS1 PRKAR2A ILK TCF7 GNG3 TLN1 PRKAR2B JUN TCF7L1 GNG4 TLN2 PRKCA KDR TCF7L2 GNG5 TRIO PLCB1 LAMA1 TGFB1 GNG7 VAV1 PLCB2 LAMB1 TGFBR1 GNG8 VCL PLCB3 LAMC1 TGFBR2 GNGT1 VEGFA PLCB4 LEF1 TLN1 GNGT2 VTN RELA LIMK1 TLN2 GRB2 WASL TNF LIMK2 TP53 GSK3B ZYX RAF1

TABLE 15 Grouped NOSE expression data compared with grouped extrapelvic implant expression data probe set id geneName direction merck2-NM_001013631_x_at HNRNPCL1 down merck-CR600442_x_at HMGB1 down merck-ENST00000361494_x_at hCG_22804 down merck2-BC051276_a_at SFRS3 down merck2-AK223241_at 7-Sep down merck-BC007887_at PGM5P2 down merck-BC013923_a_at SOX2 down merck-ENST00000342143_a_at SFRS3 down merck2-BP213746_at TMEM165 down merck-NM_005594_s_at NACA down merck2-ENST00000253490_at FAM153B down merck-XM_930195_x_at hCG_18290 down merck2-AJ890082_at HSP90AA1 down merck-NM_013269_x_at CLEC2D down merck-ENST00000273666_at STXBP5L down merck2-AA025385_x_at RPL23 down merck2-DA736876_at FXYD6 down merck2-AJ890082_x_at HSP90AA1 down merck2-DB236550_at EEF1A1 down merck-L18960_s_at EIF1AX down merck-BC085006_x_at EMID2 down merck-XM_941738_x_at hCG_1992539 down merck2-NM_005602.3_at CLDN11 down merck-NM_001004738_at OR5L1 down merck-NM_001427_at EN2 down merck-NM_174889_at NDUFAF2 down merck-BC022082_at C8orf68 down merck-ENST00000358870_s_at ANKRD20B down merck2-NM_001077358_at PDE11A down merck2-NM_001090027_x_at hCG_18290 down merck-XM_930633_x_at hCG_39912 down merck-BG501012_at NUDT22 down merck-ENST00000318825_s_at AAK1 down merck-NM_031157_x_at HNRNPA1 down merck-NM_020697_s_at KCNS2 down merck-AF305825_at GLYAT down merck-DB201122_at STK33 down merck-NM_016188_at ACTL6B down merck2-BM468600_at PCNP down merck-DR002919_at C3orf58 down merck-X96656_s_at SNORD57 down merck-XM_934781_x_at hCG_2004593 down merck-AJ315536_at LY6G6D down merck-NM_001017963_s_at HSP90AA1 down merck-hsa-mir-199a-2_at MIRN199A2 down merck-NM_022658_at HOXC8 down merck2-NM_133464_at ZNF483 down merck2-AA722645_at SOX2 down merck-ENST00000304700_x_at RPL9 down merck-AK025453_a_at PROX1 down merck-NM_138290_a_at RUNDC3B down merck-AK122845_a_at GABRG1 down merck-ENST00000382988_at RP11-408E5.4 down merck-BC027917_s_at DEFA3 down merck2-BI115886_at HSPG2 down merck-AI391567_at HIC1 down merck-NM_177980_s_at CDH26 down merck-AF170294_x_at PTMAP7 down merck2-N29174_at DIMT1L down merck-H67948_s_at ZNF335 down merck2-CR626168_at RWDD4A down merck2-NM_199425_at VSX1 down merck-AK094250_at WIPF3 down merck-ENST00000334363_s_at TXNRD2 down merck-NM_032144_s_at RAB6C down merck-NM_001018069_at SERBP1 down merck-AL133024_a_at MYT1L down merck-DA812943_at ING1 down merck-BC096084_a_at BMP6 down merck-NM_080746_at RPL10L down merck-ENST00000362017_at C1orf68 down merck-BC101970_s_at SERF1B down merck2-CB054424_at C1QL1 down merck2-NM_152460_at C17orf77 down merck-NM_053002_at MED12L down merck2-AI968309_at ANKRD55 down merck2-NM_025013_x_at ZC3H7B down merck-ENST00000373592_at ECEL1P2 down merck-BC035157_s_at ATRNL1 down merck-AB002438_at SEMA6A down merck2-AK002147_at COMMD10 down merck-NM_000870_at HTR4 down merck-ENST00000367877_at FMO9P down merck2-DB066901_at NUDT4 down merck-NM_005556_s_at KRT7 up merck2-BC018764_at KIAA1217 up merck-NM_032323_at TMEM79 up merck-NM_139204_s_at EPS8L1 up merck2-NM_032405_at TMPRSS3 up merck-NM_032405_at TMPRSS3 up merck2-BM975589_at KIAA1217 up merck2-AI582818_at SYT17 up merck2-ENST00000376317_at PRICKLE3 up merck-NM_024690_at MUC16 up merck-NM_006103_at WFDC2 up merck-NM_014398_at LAMP3 up merck-NM_003044_at SLC6A12 up merck2-CX871277_a_at QRICH1 up merck-NM_014265_at ADAM28 up merck-DA804924_a_at PTPN1 up merck-NM_020805_at KLHL14 up merck-NM_021136_at RTN1 up merck-NM_024626_at VTCN1 up merck-NM_017821_at RHBDL2 up merck2-AK027845_at ZNF682 up merck-NM_004947_at DOCK3 up merck-NM_002423_at MMP7 up merck2-AK075533_at C1QTNF3 up merck-NM_001031615_at ALDH3B2 up merck2-DQ893132_at MMP7 up merck-NM_130446_at KLHL6 up merck-NM_018088_x_at FAM90A1 up merck-NM_177964_at LYPD6B up merck-ENST00000285013_a_at SLFN13 up merck2-NM_032405_a_at TMPRSS3 up merck-NM_006586_at CNPY3 up merck-BC001060_a_at PAX8 up merck-NM_153255_at MCM9 up merck-NM_144505_s_at KLK8 up merck-NM_138804_at C2orf65 up merck-NM_002534_a_at OAS1 up merck-NM_014474_at SMPDL3B up merck2-NM_144507_a_at KLK8 up merck-NM_005447_at RASSF9 up merck-BC050704_s_at DCDC2 up merck-NM_019043_at APBB1IP up merck-ENST00000382056_a_at C1QTNF3 up merck-NM_001013622_at FAM53A up merck-NM_004112_at FGF11 up merck-NM_153338_at GGT6 up merck-NM_005560_s_at LAMA5 up merck-NM_002885_at RAP1GAP up merck-NM_000804_at FOLR3 up merck2-AI695443_at LPCAT3 up merck-CD359695_a_at ATRN up merck-NM_172341_at PSENEN up merck2-AL570385_at ELL up merck-NM_172374_at IL4I1 up merck-NM_001692_at ATP6V1B1 up merck2-NM_198586_at NHLRC1 up merck-NM_000493_at COL10A1 up merck-AK055763_a_at RASSF4 up merck-NM_003480_at MFAP5 up merck-NM_013992_at PAX8 up merck2-AF109683_a_at LAIR1 up merck2-AL531282_at NUCB1 up merck-NM_000616_at CD4 up merck-NM_199161_s_at SAA1 up merck-NM_013404_at MSLN up merck2-NM_031460_at KCNK17 up merck-AW016260_s_at SLC2A9 up merck-NM_005046_s_at KLK7 up merck-NM_033635_at SCAND2 up merck-U52696_a_at ATF6B up merck-NM_001852_at COL9A2 up merck-NM_152517_s_at TTC30B up merck2-BQ188534_at MTF1 up merck-DB058745_a_at SMARCA4 up merck2-NM_172208_at TAPBP up merck-NM_016725_s_at FOLR1 up merck2-AI813450_at CDH6 up merck-AK056597_s_at OTUD4 up merck2-BU676864_at KIAA0226 up merck2-NM_001009568_at SMPDL3B up merck-NM_024508_at ZBED2 up merck-NM_198586_at NHLRC1 up merck-NM_174959_s_at SVOPL up merck-NM_001024941_at TRIM17 up merck-NM_005940_s_at MMP11 up merck2-NM_024022_at TMPRSS3 up merck-CR602026_a_at ZNRF1 up merck-NM_000540_at RYR1 up merck-AB051390_a_at SPON1 up merck2-NM_013372_at GREM1 up merck-NM_001005336_s_at DNM1 up merck-NM_005668_at ST8SIA4 up merck2-XM_209144_a_at LYPD5 up merck-NM_006509_at RELB up merck-NM_000379_s_at XDH up merck2-AK095290_at CP up merck-NM_022162_at NOD2 up merck-NM_017450_at BAIAP2 up merck2-NM_005060_at RORC up merck-NM_032383_at HPS3 up merck2-NM_024592_at SRD5A3 up merck2-F10838_at PRR4 up merck2-BQ217998_a_at ANKLE2 up merck-CB529328_s_at GBP4 up merck-NM_206818_s_at OSCAR up merck2-AK125566_at FAM53A up merck2-AL534327_at BCAM up merck-NM_052813_s_at CARD9 up merck2-AK025905_at SOX17 up merck-BC049195_a_at ELL up merck-NM_032534_at KRBA1 up merck2-BU608654_at ATP6V1B1 up merck2-DA404651_at ZNF490 up merck2-XM_092778_at TTLL9 up merck-NM_005951_x_at MT1H up merck-NM_000941_at POR up merck-NM_003041_at SLC5A2 up merck-DA736753_a_at BAT2D1 up merck-NM_031310_at PLVAP up merck-XM_945048_s_at C1orf186 up merck2-NM_014395_at DAPP1 up merck2-NM_005409_at CXCL11 up merck-NM_001039477_s_at C1orf38 up merck2-BE676460_at C11orf80 up merck-NM_001878_at CRABP2 up merck-ENST00000373692_a_at PTGS1 up merck2-BC029840_at PTGS1 up merck-NM_080669_a_at SLC46A1 up merck-AB209742_at PARP9 up merck2-DA944610_at ACOX1 up merck2-U04343_at CD86 up merck-NM_020370_at GPR84 up merck-BC003072_at RET up merck2-CR983377_at ZFR up merck2-DA944610_x_at ACOX1 up merck-BX365476_s_at TMPRSS3 up merck-NM_000734_at CD247 up merck2-AK223068_at SECTM1 up merck-NM_000424_at KRT5 up merck-ENST00000354705_a_at PTPRF up merck-NM_144657_at HDX up merck-AK056035_a_at SMG7 up merck-CA776036_s_at EWSR1 up merck-BC000801_at CFLAR up merck2-M19922_at FBP1 up merck-NM_024501_at HOXD1 up merck-NM_024817_at THSD4 up merck-NM_001018072_at BTBD11 up merck-NM_001572_at IRF7 up merck-NM_001012642_at GRAMD2 up merck-NM_004712_at HGS up merck2-NM_016816_at OAS1 up merck-NM_001039659_s_at IL18BP up merck-NM_022054_at KCNK13 up merck-DB370515_s_at ADD2 up merck-NM_004950_at EPYC up merck-AL832920_a_at KIAA1618 up merck-NM_000096_s_at CP up merck-NM_201630_at LRRN2 up merck-AK056725_s_at ACVRL1 up merck2-NM_017670_at OTUB1 up merck-NM_015645_at C1QTNF5 up merck-NM_173660_at DOK7 up merck-NM_024572_s_at GALNT14 up merck-NM_001517_s_at GTF2H4 up merck-NM_173831_s_at ZNF707 up merck-NM_145313_at RASGEF1A up merck-NM_004204_at PIGQ up merck-BX416440_a_at CLSTN1 up merck2-NM_182573_at LYPD5 up merck-NM_001017403_at LGR6 up merck-NM_016523_at KLRF1 up merck-NR_002598_x_at SNORD87 up 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merck-NM_016151_s_at TAOK2 up merck2-NM_080657_at RSAD2 up merck-NM_005132_at REC8 up merck2-AI431558_x_at MFI2 up merck-BC023558_a_at SPOCK2 up merck-NM_000639_at FASLG up merck2-BQ893829_at NAGLU up merck2-XM_374898_at PCNXL3 up merck-NM_014405_at CACNG4 up merck-AK098385_s_at RTN4 up merck-CR936744_at HOMER2 up merck-BC039860_at CHD6 up merck-NM_024650_at C11orf80 up merck-AF061935_a_at VPRBP up merck2-AL832190_at COG2 up merck2-BI519527_at IKZF1 up merck2-AL515469_s_at NANS up merck-BC065197_at PUS10 up merck2-BC041388_at ZNF553 up merck-NM_03205 l_s_at PATZ1 up merck2-ENST00000368925_at DDO up merck-NM_005892_at FMNL1 up merck-NM_016830_s_at VAMP1 up merck-BU542820_at GALNT6 up merck-CR992676_s_at ZC3H11A up merck-BC050321_a_at TBC1D1 up merck-NM_001039468_s_at MARK2 up merck2-AI971668_a_at SMAD6 up merck-NM_030792_s_at GDPD5 up merck2-BU622650_a_at BHLHB3 up merck-NM_005949_s_at MT1F up merck2-ENST00000366969_at VASH2 up merck-NM_152225_s_at PPEF1 up merck-NM_152511_at DUSP18 up merck-NM_080605_at B3GALT6 up merck2-XM_001133198_x_at FCGR1A up merck-NM_001610_at ACP2 up merck-NM_032782_at HAVCR2 up merck-NM_001004431_at METRNL up merck-AF143684_s_at MYO9B up merck-X96660_s_at RAB26 up merck-NM_024909_a_at C6orf134 up merck-NM_018245_at OGDHL up merck2-BM561748_at GZMB up merck2-ENST00000360922_at C1orf56 up merck-ENST00000361686_at ST6GAL2 up merck-ENST00000355436_at ZNF252 up merck-NM_012427_at KLK5 up merck-BC009714_a_at RAB39B up merck-NM_003834_at RGS11 up merck-NM_002986_s_at CCL11 up merck-BQ420304_a_at SETD1B up merck-NM_015925_at LSR up merck2-AL136709_at ABI3 up merck-NM_178181_a_at CDCP1 up merck-BC094869_x_at hCG_20426 up merck-NM_021209_s_at NLRC4 up merck-NM_019601_at SUSD2 up merck-AX747748_s_at IGHA1 up merck2-AU120661_at ARHGEF3 up merck-NM_003986_at BBOX1 up merck-ENST00000310260_a_at VANGL1 up merck-NM_145214_at TRIM11 up merck-NM_006768_at BRAP up merck2-NM_018986_at SH3TC1 up merck-NM_015568_at PPP1R16B up merck-NM_017636_s_at TRPM4 up merck-AB209400_at UQCC up merck-NM_012396_at PHLDA3 up merck-NM_014807_s_at C2CD2L up merck-NM_207362_at C2orf55 up merck-BC028212_at PIK3R5 up merck-BC033255_x_at IL8RBP up merck-NM_032034_at SLC4A11 up merck-AW072050_a_at MYO9B up merck-BC034402_a_at RBM47 up merck-BC020867_at SLC6A13 up merck2-R42193_a_at NDRG4 up merck-NM_022744_at C16orf58 up merck-X96653_s_at SNORD54 up merck-NM_015039_at NMNAT2 up merck-NM_013447_at EMR2 up merck2-XM_001128702_at SGPP2 up merck-NM_023930_at KCTD14 up merck-NM_006277_s_at ITSN2 up merck-NM_018936_at PCDHB2 up merck-NM_002407_at SCGB2A1 up merck-NM_016929_at CLIC5 up merck2-BC084547_at NCKAP1L up merck-AK097258_s_at DOK3 up merck-ENST00000325348_s_at C8orf30A up merck-NM_005978_at S100A2 up merck-NM_145000_at RANBP3L up merck-NM_001782_at CD72 up merck2-CB055265_at CD81 up merck2-NM_002917_at RFNG up merck2-BX647769_at ANKRD36 up merck-NM_005950_s_at MT1G up merck-NM_018226_at RNPEPL1 up merck-BC070352_x_at IGLV3-21 up merck2-BU564645_at STAG2 up merck-NM_152386_a_at SGPP2 up merck-NR_002736_s_at RAB26 up merck2-CR976782_at AHNAK up merck2-BC009851_at IGHM up merck2-NM_033130_at SIGLEC10 up merck-NM_003914_at CCNA1 up merck-AK095776_a_at THRB up merck-NM_005562_at LAMC2 up merck2-NM_198490_at RAB43 up merck-NM_031244_at SIRT5 up merck-AK023855_at PAX8 up merck-XM_936535_at NDOR1 up merck-NM_024947_at PHC3 up merck-ENST00000260257_at FDXACB1 up merck-NM_015481_s_at ZNF385A up merck-NM_080616_a_at C20orf112 up merck-ENST00000375678_s_at C20orf112 up merck2-W94916_at CTDSPL up merck2-BF914623_at CFLAR up merck-NM_016356_at DCDC2 up merck2-NM_182756_at SPDYA up merck-NM_005241_a_at EVI1 up merck-CN335383_a_at TBC1D1 up merck2-DC428989_at HNRNPK up merck2-NM_212479_at ZMYND11 up merck2-ENST00000376573_at PIP4K2A up merck-NM_032207_at C19orf44 up merck-NM_007121_at NR1H2 up merck-NM_020944_at GBA2 up merck-ENST00000372765_a_at CAMK2G up merck2-BC002829_at S100A2 up merck-NM_002769_s_at PRSS1 up merck-NM_001040424_at PRDM15 up merck-AF390894_a_at SLAMF7 up merck-BC013107_at WDR42A up merck2-DB293898_a_at BAZ2A up merck-ENST00000361975_a_at SETD2 up merck2-BM838001_at RAB8A up merck-NM_004409_s_at DMPK up merck-NM_001683_a_at ATP2B2 up merck-AK097071_s_at IGHM up merck-NM_021228_at SCAF1 up merck2-BX648451_at KIAA1217 up merck-BCl11487_a_at TTC7A up merck-BC029891_a_at TFEC up merck-NM_015852_at ZNF117 up merck-NM_017865_s_at ZNF692 up merck-BC014211_x_at TCEA2 up merck-G30809_at ARF5 up merck2-BU634330_at NCK1 up merck-NM_152604_s_at ZNF383 up merck-BG677853_a_at LAMC2 up merck-NM_133178_at PTPRU up merck-NM_153022_s_at C12orf59 up merck-NM_014270_at SLC7A9 up merck-BP195474_a_at SPOCK2 up merck-NM_005512_at LRRC32 up merck2-CN429342_at RERE up merck2-DQ892684_at ITGB2 up merck-NM_005248_s_at FGR up merck-NM_019110_s_at ZKSCAN4 up merck-NM_007188_at ABCB8 up merck-AF043143_s_at IL1RN up merck-NM_019092_s_at FAM63B up merck-NM_007181_at MAP4K1 up merck-ENST00000367602_at QSOX1 up merck2-AJ012501_at STX11 up merck-ENST00000375799_at PLEKHM2 up merck-NM_148966_at TNFRSF25 up merck-NM_014211_at GABRP up merck-NM_006147_at IRF6 up merck2-NM_015474_at SAMHD1 up merck-NM_000647_s_at CCR2 up merck2-NM_002020_at FLT4 up merck-ENST00000377746_at SLC45A4 up merck2-AK025676_a_at RNF213 up merck2-BY795924_at AKAP8L up merck-NM_182557_s_at BCL9L up merck-NM_032663_a_at USP30 up merck-NM_033204_at ZNF101 up merck-NM_001009941_a_at ANKRD16 up merck2-AY312431_at SGMS1 up merck-ENST00000313975_s_at CSNK1G2 up merck2-AI918932_s_at ENTPD1 up merck-NM_001001430_s_at TNNT2 up merck-CD672190_a_at PLCE1 up merck-NM_007162_s_at TFEB up merck2-NM_015488_a_at PNKD up merck-AK027045_at ZBTB3 up merck-AK095013_at SLC8A1 up merck2-NM_172231_x_at SF4 up merck-NM_001488_s_at TADA2L up merck-NR_002437_s_at SNORD54 up merck-NM_017576_at KIF27 up merck-L43092_x_at IGLV3-19 up merck2-DA660473_at BIRC2 up merck-NM_152609_s_at C1orf71 up merck-AK127693_s_at PLCB1 up merck-NM_024886_at C10orf95 up merck-NM_004362_at CLGN up merck2-NM_001045556_at SLA up merck-CR591922_a_at FCGR1A up merck-BC002976_s_at CYB561 up merck-AI218739_at CCDC123 up merck-NM_018950_x_at HLA-F up merck2-BC009418_at CHODL up merck-NM_018423_at STYK1 up merck-BC050449_a_at ARFGEF2 up merck-NM_138352_a_at SAMD1 up merck-NM_000216_at KAL1 up merck2-DQ892100_a_at CLGN up merck-AY260572_a_at FLVCR2 up merck2-NM_023930_at KCTD14 up merck-NM_022147_at RTP4 up merck-NM_024015_at HOXB4 up merck2-AB208798_at PSD4 up merck-NM_001454_at FOXJ1 up merck-DA674734_a_at VCL up merck2-EL734573_a_at TRAF3IP1 up merck-NM_016464_at TMEM138 up merck2-NM_018179_at ATF7IP up merck-NM_022872_at IFI6 up merck-ENST00000299927_a_at ZNF592 up merck-NM_015650_a_at TRAF3IP1 up merck-AK090648_x_at ZNF273 up merck-NM_003064_at SLPI up merck2-AL541942_x_at NOTCH3 up merck-NM_001040031_at CD37 up merck2-NM_014687_at KIAA0226 up merck-NM_018089_at ANKZF1 up merck-NM_033104_a_at STON2 up merck-NM_005258_at GCHFR up merck-NM_004838_at HOMER3 up merck-NM_019085_at FBXL19 up merck2-DA731322_at RBAK up merck-NM_025231_at ZSCAN16 up merck-NM_017434_at DUOX1 up merck-NM_002251_at KCNS1 up merck2-ENST00000358605_at REST up merck-CR602154_s_at RNASEH2C up merck-NM_001024593_at ZMYND17 up merck-NM_001017981_at RNF215 up merck-NM_003042_at SLC6A1 up merck-U37283_s_at MFAP5 up

Expression of the TGF-WNT/cytoskeleton remodeling pathway was associated with survival from OVCA (n=218, P=0.006, FIG. 2A), colon cancer (n=177, P=0.004, FIG. 2B), and leukemia (n=182, P=0.047, FIG. 2C). The chemokines/cell adhesion pathway was associated with survival from colon cancer (n=177, P=0.005, FIG. 3), and the histamine signaling/immune response pathway was associated with survival from OVCA (n=142, P<0.001, FIG. 4A) and colon cancer (n=177, P=0.02, FIG. 4B).

Inhibition of the TGF-WNT/Cytoskeleton Remodeling Pathway Prevents Cell Migration

In light of the TFG-WNT/cytoskeleton remodeling pathway expression associations and its influence on metastatic activity in other cancer types, functional studies were performed to evaluate the effect of this pathway on OVCA cellular metastatic characteristics, specifically the influence of inhibition of this pathway using artesunate (Akhmetshina A, et al. Nat Commun 2012 3:735; Li P C, et al. Cancer Res 2008 68:4347-51) on OVCA cell migratory ability. Inhibition of TGF-WNT signaling using 25 mM or 50 mM artesunate decreased HeyA8 OVCA cell proliferation by approximately 42% and 64%, respectively, and impaired the ability of the cells to migrate into the denuded area (FIG. 5). In contrast, cells cultured in media containing DMSO vehicle completely filled in the gap within 2 days (FIG. 5).

Comments

The above findings indicate that advanced-stage OVCA has a unifocal origin in the pelvis. Disclosed are pathways associated with metastasis of OVCA as well as metastasis/recurrence and overall survival from multiple human cancers. These functional studies suggest that such pathways represent appealing therapeutic targets for patients with metastatic disease.

The p53 gene is known to be mutated in 30-80% of OVCAs (Okamoto A, et al. Cancer Res 1991 51:5171-6; Salani R, et al. Int J Gynecol Cancer 2008 18:487-91). Because there is a strong selection for these mutations to be distributed over the conserved regions of the gene, the sequence of p53, exons 5-8 was compared. Of 30 primary pelvic lesions tested, 11 (37%) containing DNA mutations. In every case, the matched extrapelvic implant contained an identical mutation. Subsequently, analysis of allele loss on chromosome 17 in 16 OVCA samples revealed identical patterns of allelic deletions in all samples resected from the same patient, irrespective of the collection site (Tsao S W, et al. Gynecol Oncol 1993; 48:5-10). In 4 of 16 informative samples, the analysis of the hypoxanthine phosphoribosyl transferase gene showed that the same parental allele was methylated in samples collected from the primary and metastatic sites (Tsao S W, et al. Gynecol Oncol 1993 48:5-10).

The data generated here support a unifocal origin of advanced-stage OVCA. Moreover, 3 pathways (TGF-WNT/cytoskeleton remodeling, chemokines/cell adhesion, and histamine signaling/immune response) were identified that are not only associated with advanced, metastatic, or recurrent disease but also with overall survival from a range of cancers.

Unless defined otherwise, all technical and scientific terms used herein have the same meanings as commonly understood by one of skill in the art to which the disclosed invention belongs. Publications cited herein and the materials for which they are cited are specifically incorporated by reference.

Those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, many equivalents to the specific embodiments of the invention described herein. Such equivalents are intended to be encompassed by the following claims. 

1. An in silico method to identify therapeutic agents to treat cancer, comprising: (a) evaluating gene expression datasets to identify genes differentially expressed in cancer and/or metastatic cells, (b) identifying molecular pathways represented by the differentially expressed genes, (c) evaluating the molecular pathways for associations with metastasis and/or cancer survival as an indication of biological relevance, and (d) identifying agents or drugs that have activity against the pathways associated with metastasis and/or cancer survival.
 2. The method of claim 1, wherein step (a) comprises identifying genes whose expression is increased or decreased in the cancer cells by at least 100%.
 3. The method of claim 1, wherein the genes are identified with a False Discovery Rate (FDR) less than 0.05.
 4. The method of claim 1, wherein step (b) comprises the use of principal component analysis (PCA) to summate the expression of each molecular pathway in cancer survival datasets into a single numeric value.
 5. The method of claim 1, wherein the cancer is an epithelial cancer.
 6. The method of claim 5, wherein the cancer is ovarian cancer.
 7. The method of claim 1, wherein the molecular pathways are selected from the group consisting of TGF-WNT/cytoskeleton remodeling pathway, WNT2 pathway, integrin pathway, chemokines/cell adhesion pathway, and histamine signaling/immune response pathway.
 8. The method of claim 1, wherein step (d) comprises in silico screening of a database of candidate agents catalogued by molecular pathway activity.
 9. The method of claim 1, wherein step (d) comprises repurposing a drug not previously used to treat cancer.
 10. A in silico method for selecting cancer treatment regimen for a subject, comprising: (a) assaying an RNA sample from a tumor biopsy of the subject to identify genes differentially expressed compared to a control; (b) identifying molecular pathways represented by the differentially expressed genes, (c) generating a score that summarizes the overall gene expression of one or molecular pathways comprising differentially expressed genes; and (d) selecting a cancer treatment regimen for the subject based on the molecular pathways associated with the subject's cancer.
 11. The method of claim 10, wherein step (a) comprises identifying genes whose expression is increased or decreased in the cancer by at least 100% compared to the control.
 12. The method of claim 10, wherein the genes are identified with a False Discovery Rate (FDR) less than 0.05.
 13. The method of claim 10, wherein step (c) comprises the use of principal component analysis (PCA) to summate the expression of the one or more molecular pathways into a single numeric value.
 14. The method of claim 10, wherein the cancer is ovarian cancer.
 15. The method of claim 10, wherein the one or more molecular pathways are selected from the group consisting of TGF-WNT/cytoskeleton remodeling pathway, WNT2 pathway, integrin pathway, chemokines/cell adhesion pathway, and histamine signaling/immune response pathway. 